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BACKGROUND
We are looking for a motivated and experienced Bioinformatics Analyst to join Dr. Robert Burk's research group. This role is critical for supporting our ongoing research projects focused in 2 areas- the human microbiome (gut, oral and cervicovaginal), and human papillomavirus-related to cervix neoplasia. The ideal candidate will have a background in epidemiology, computer science, bioinformatics, or related disciplines, with practical demonstrated experience in processing next-generation sequencing (NGS) data. The successful candidate will demonstrate a willingness and eagerness to adapt to new approaches, as the field of bioinformatics is dynamic and constantly evolving.
RESPONSIBILITIES
Key Responsibilities in order of priority:
- NGS Data Handling: Perform demultiplexing and analysis of NGS data using barcoding primers for multiplex NGS runs.
- Practical Experience: The candidate is expected to have practical experience with bioinformatics work (handling NGS reads off the machine, etc.) and be willing and eager to adapt to new approaches. This role will be facilitated with a proactive attitude towards learning and applying new bioinformatics methods and technologies.
- Data Processing and Analysis: Utilize existing pipelines to process and analyze high-throughput sequencing data reads, including amplicon sequencing, bisulfite sequencing, metagenomics, and viral integration.
- Data Management: Manage and organize bioinformatics sequencing data for our research group, including papillomavirus sequences, microbiome data (16S, ITS1 and shotgun metagenomics), and human genomic data.
- Large Dataset Management: Download and handle large Fastq, BAM, and/or Fasta files for analyses.
- Software Utilization and Script Modification: Use existing software tools and be able to modify R scripts to generate figures and perform epidemiological analyses.
- Phylogenetic Analysis: Construct phylogenetic trees to support ongoing research projects.
- Collaboration and Reporting: Work closely with and report directly to Robert D. Burk, M.D., Principal Investigator, and collaborate with other lab members generating NGS data.
REQUIREMENTS
Minimum Education: BS/Undergraduate
Minimum Experience: 1-2 Years
Required Travel: 0-10%
- Educational Background: Bachelor's degree with at least one year of experience in epidemiology, computational biology, or bioinformatics.
- Technical Skills: Proficiency in R or Python is required. Experience in microbiome bioinformatic processing is preferred.
- Communication Skills: Ability to speak clearly and express oneself well in one-on-one conversations and groups. Develops effective written communications and uses them appropriately. Ability to present at weekly lab meetings using PowerPoint or other presentation programs.
- Interpersonal Skills: Interacts and proactively shares information with internal and external contacts where appropriate. Develops effective professional relationships with peers, students, and employees.
- Responsibility and Problem-Solving: Assumes responsibility to ensure issues/concerns are addressed and monitors them through to conclusion. Identifies, defines, and analyzes information and situations before recommending a course of action.
- Time Management: Effectively manages own time and resources.
- Innovation and Technology: Seeks to apply technology and innovation to improve efficiency and solve problems related to the goals of the research group.
LOCATION
Bronx, New York, 10461 United States
COMPENSATION
$60,000 Yearly Salary
DEADLINE
9/7/2024
PI244887266
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BACKGROUND
The Stanford University School of Medicine (SoM) is recruiting multiple faculty at the Assistant, Associate, or Full Professor in the University Tenure Line (UTL), University Medical Line (UML), or Non-Tenure Line-Research (NTL-R) through this AI (Artificial Intelligence) Faculty Cluster Hire Search. We are specifically interested in candidates who have experience developing and applying novel biomedical AI and data science methods that incorporate biomedical domain expertise to ensure relevance and impact to health and medicine. Candidates will be hired into one or more SoM department(s) and contribute to the research, educational, and if relevant, clinical activities.
This AI Faculty Cluster Hire Search aims to recruit a diverse group of experts dedicated to fostering growth of biomedical AI and data science both within our organization and beyond. These distinguished individuals will become integral members of a dynamic community, collaborating not only within their respective departments or institutes but also across the SoM and our university at large.
REQUIREMENTS
- The predominant criterion for appointment in the University Tenure Line is a major commitment to research and teaching.
- The major criteria for appointment for faculty in the University Medical Line shall be excellence in the overall mix of clinical care, clinical teaching, scholarly activity that advances clinical medicine, and institutional service appropriate to the programmatic need the individual is expected to fulfill.
- The major criterion for appointment for faculty in the Non-tenure Line (Research) is evidence of high-level performance as a researcher for whose special knowledge a programmatic need exists.
Faculty line and rank will be determined by qualifications and experience. The successful candidate must have an MD, MD/PhD, or PhD with substantial expertise in one or more aspects of biomedical data science enabled or enhanced by AI. The successful candidate will be expected to develop an independent research program that advances AI approaches to biomedical data science, with a focus on their use in basic, translational, clinical, and/or population sciences.
FOCUS AREAS & RESPONSIBILITIES
Examples of focus areas in basic science research include development of methods to determine molecular structures, accelerate development of novel therapeutics, elucidate stem cell biology, or enable regenerative medicine. Examples of focus areas in clinical research include the development of AI methods for integration and analysis of multimodal patient data, including laboratory tests, clinical notes, images and video across multiple scales, speech to text, physiologic assays, and functional evaluations. Clinical AI research domains span across medical specialties, including but not limited to cancer, neurology, neuroscience, cardiovascular disease, intensive care, mental health, peri-operative care, pain management, ophthalmology, pediatrics, radiology, pathology, and surgery. Examples of focus areas in population health research include pharmacoepidemiology, genetic epidemiology, environmental epidemiology, AI health policy, fairness, and the legal, regulatory, ethical, and economic considerations that underlie the responsible implementation of clinical decision support tools. Research in all of these areas will benefit from broad interactions and collaborations throughout the SoM, across Stanford University, and within the large and growing health systems of Stanford Medicine.
The successful candidate will be expected to teach students, residents, postdoctoral fellows and clinical fellows, and participate in relevant clinical and basic science conferences. They will have demonstrated the potential to achieve, or have a demonstrated record of achievement in relevant rigorous research. The Departments, School of Medicine, and Stanford University value faculty who will help foster an inclusive academic environment for colleagues, students, and staff with a wide range of backgrounds, identities, and outlooks. Candidates may choose to include as part of their research and teaching statements a brief discussion about how their work and experience will further these ideals. Additional information about Stanford's IDEAL initiative may be found here: https://ideal.stanford.edu/about-ideal.
COMPENSATION
This role is open to candidates from multiple disciplines/specialties. The pay offered to the selected candidate will be based on their field or discipline. The expected base pay range for likely disciplines are listed below. Interested candidates whose discipline is not listed below may contact the hiring department for the salary range specific to their discipline/specialty.
PhD, Basic Science:
Assistant: $185k - $203k
Associate: $218k - $242k
Professor: $266k - $296k
PhD, Data Science or related field:
Assistant: $215k - $242k
Associate: $258k - $285k
Professor: $307k - $332k
MD, Research-Only (see below for further clarification):
Assistant: $190k - $208k
Associate: $218k - $242k
Professor: $261k - $279k
This pay range reflects base pay, which is based on faculty rank and years in rank. It may not include all components of faculty compensation or pay from participation in departmental incentive compensation programs. These scales do not include compensation for clinical practice, which may be relevant to specific candidates and departments. For more information about compensation and our wide-range of benefits, including housing assistance, please contact the hiring department.
Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years in rank, training, and field or discipline; internal equity; and external market pay for comparable jobs.
HOW TO APPLY
Review of complete applications will begin on September 23, 2024, and will continue until the positions are filled.
Interested candidates should submit the following to: https://facultypositions.stanford.edu/cw/en-us/job/494741/.
1. A detailed letter of research and teaching interest and if relevant, clinical specialty
2. A curriculum vitae
3. Three names of referees for letters of recommendation
POLICY
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from others who would bring additional dimensions to the University's research, teaching and clinical missions.
Curt Langlotz, Professor of Radiology
Natalie Pageler, Clinical Professor of Pediatrics
Nima Aghaeepour, Associate Professor Anesthesiology, Perioperative and Pain Medicine
Olivier Gevaert, Associate Professor of Medicine
Search Committee Co-Chairs
Stanford University School of Medicine
For questions or issues with filling out the application, please contact bscacademicaffairs[at]stanford.edu. Please note, this inbox cannot answer questions regarding application status.
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BACKGROUND
The Department of Biology at Occidental College invites applications for two tenure‐track Assistant Professors of Cellular and/or Molecular Biology with appointment to begin August 2025.
RESPONSIBILITIES
The Department of Biology at Occidental College invites applications for two tenure‐track positions at the rank of Assistant Professor in any area of Cellular and/or Molecular Biology. We seek teacher-scholars who are committed to 1) developing a research program in molecular and/or cellular biology that engages undergraduate students, 2) excellence and innovation in teaching, and 3) promoting inclusivity in both research and teaching.
Occidental faculty are committed teacher-scholars who bring research and creative discovery to life for students in classrooms, labs, studios, and mentored projects. They teach broadly in the curricula of their departments, advise students, carry out research and creative work, and provide departmental, college-wide, and external service. In this position, your primary responsibilities will include the development and teaching of introductory and core courses in the discipline, including courses in your area(s) of specialization. Specific courses that you will teach include introductory and intermediate cellular and molecular biology courses, with the opportunity to develop upper-division courses in speciality areas. You will also be responsible for producing scholarship commensurate with the requirements for tenure, and will be expected to develop a program of research that engages undergraduate students. You will also be expected to contribute to and participate in the life and development of the department, advise students, serve on committees, and participate in the broader college and disciplinary communities.
REQUIREMENTS
- A Ph.D. in Cellular and/or Molecular Biology or a related science discipline
- Evidence of impactful peer-reviewed scholarly research and publications in the field of Cellular and/or Molecular Biology
- Compelling vision for developing a wet lab research program that integrates undergraduate training and mentoring, with potential to attract extramural funding
- Demonstrated commitment to, past evidence of, and future plans for effective teaching and mentoring in the undergraduate setting. Please do not include individual teaching evaluations
- Demonstrated commitment to, past evidence of, and future plans for creating and advancing equitable opportunities for learning and mentoring, especially for students from historically marginalized groups
- Ability to present scientific ideas clearly, in both verbal and written formats, at an appropriate level for the audience
- Commitment to collaborating effectively with colleagues across specialties, departments, or disciplines
PREFERENCES
- Postdoctoral research and/or postdoctoral teaching experience
- Ability to leverage College resources (e.g., genomics center, high-performance computer cluster, or natural history collections) or nearby facilities or natural resources in the Southern California area for research and/or broader impacts
- Prior experience teaching and or mentoring undergraduates
- Demonstrated commitment to engaging broader societal impacts of the scholarly research, e.g., local outreach and community engagement
- Experience teaching and utilizing bioinformatics approaches in the classroom and/or research program
- Prior experience collaborating with colleagues across specialties, departments, or disciplines
- Ability to teach and collaboratively work with campus-based colleagues in departments and programs including Biochemistry, Computer Science, Chemistry, Cognitive Science and Public Health
TERMS
Full-time, tenure-track
COMPENSATION
$85,000-$92,000
HOW TO APPLY
Submit the following materials through Interfolio (https://apply.interfolio.com/150510) to be considered by the search committee. An application includes the following:
- Cover letter
- This letter describes your interest in the position, and the education, experience, and skills you possess that demonstrate your ability to meet all required qualifications and if applicable, preferred qualifications.
- Curriculum Vitae
- Research Statement of ~2 pages
- This statement provides an overview of your current research program and a vision for a future research program at Occidental, including how you will incorporate undergraduate students into the research program
- Teaching Philosophy Statement of ~2 pages
- This statement provides an overview of your teaching philosophy, preferred pedagogical practices, and prior experiences in teaching and mentoring. Please do not include student evaluations.
- Commitment to Inclusive Excellence Statement of ~1 page
- This statement provides your unique perspective on your past and present contributions to and future aspirations for promoting justice, equity, inclusion, and diversity in your professional career. This should include your demonstrated commitment to, past evidence of, and future plans for creating equitable opportunities for learning and mentoring especially for students from marginalized and minoritized groups. You may also speak to how your research and/or service promotes justice, equity, inclusion, and diversity. The purpose of this statement is to help the department identify candidates who have professional experience, intellectual commitments, and/or willingness to engage in activities that could help the College contribute to its mission in these areas.
- List of three references with relevant contact information
- If you advance to the finalist phase, you will be asked to have each of your three references submit a letter of recommendation. Please be prepared to have your referents submit their letters should you move forward to this phase of the search. Do not submit these letters with your initial application.
DEADLINE
To be assured full consideration, your application materials must be received by September 30, 2024.
POLICY
Occidental is an Equal Opportunity Employer and does not unlawfully discriminate against employees or applicants on the basis of race, color, religion, sex, sexual orientation, gender identity, gender expression, pregnancy, breastfeeding or related medical condition, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, genetic characteristic or information, military and veteran status, or any other characteristic protected by state or federal law. Occidental is strongly committed to increasing the diversity of the campus community and the curriculum, and to fostering an inclusive, equitable, and just environment within which students, staff, administrators, and faculty thrive. Candidates who can contribute to this goal through their teaching, research, advising, and other activities are encouraged to identify their strengths and experiences in this area. Individuals advancing the College's strategic equity and justice goals and those from groups whose underrepresentation in the American professoriate has been severe and longstanding are particularly encouraged to apply.
Salary is commensurate with experience and qualifications. Moving expense reimbursement (up to $5000, taxable according to current IRS regulations), start-up funds, and a one-course reduction of teaching load in the first year are provided. A comprehensive benefits package is available that includes: excellent health, dental, life, and retirement benefits; tuition benefits for the employee, spouse, domestic partner, and dependents; additional extras including use of gym facilities and the College Library. For a detailed description of benefits, please visit https://www.oxy.edu/offices-services/human-resources/benefits-information.
All qualified applicants who submit a complete application by the deadline will be considered for employment, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance.
Occidental College is committed to working with and providing reasonable accommodations to applicants with qualifying disabilities. If you need a reasonable accommodation because of a disability for any part of the application or employment process, please contact Human Resources (hr[at]oxy.edu).
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BACKGROUND
This is a 3-year PhD position, that is part of a European Doctoral Network (DN) program entitled "Prostate cancer omics mediated intervention (PROMOTE)" involving 13 research centres from Germany, Greece, Austria, Portugal, and Spain.
The PhD position is hosted at Delta 4 GmbH, Vienna, Austria.
The PROMOTE Consortium / Background:
PROMOTE focuses on the multidisciplinary education of doctoral candidates (DCs) in -omics and artificial intelligence (AI) mediated intervention to improve the clinical management of Prostate Cancer (PCa). PCa is the second most common malignancy, affecting ~1.3 million men every year worldwide. Tragically, there is a treatment paradox, as ~45% of PCa patients experience slow-growing cancer and are unlikely to progress rapidly, while PCa is not curable at an advanced stage. Evidently, clinical management of PCa is not optimal, as patients who do not require treatment are over-treated, while for those where immediate actions are required, efficient treatment is still needed. To fill the above gaps, PROMOTE was formed to educate DCs in emerging -omics and AI technologies and deliver:
1. Novel non-invasive tools (based on biomarker- and AI- models) to guide intervention, and
2. More efficient treatment options for advanced PCa (particularly metastatic) driven by molecular characterization of the disease phenotypes.
PROMOTE brings together 13 leading centres from different disciplines, including 3 SMEs, 4 university hospitals with clinical laboratories, and 2 research institutes, and 4 universities, closely collaborating with a solid scientific background, as demonstrated by multiple publications.
PROMOTE research builds on:
1. Available biobanks and -omics datasets within the PROMOTE consortium, including >3000 urinary proteomics, >1100 imaging datasets paired with biopsy and pathology data, >350 paired RNA and proteomics urinary profiles, >100 tissue proteomics and ~300 phospho-, proteo-genomic and transcriptomics profiles from public repositories
2. Established software and analytical protocols on -omics data integration, AI feature extraction and integration, systems biology, pathway enrichment, drug repurposing and in vitro testing, and
3. Infrastructure to support hosting and training of DCs.
The PROMOTE partner hosting the PhD student:
Delta 4 GmbH is a Vienna-based TechBio company at the forefront of digital drug discovery and development. Delta4 leverages a proprietary computational analytics platform (Hyper-C), combined with biomedical testing and clinical validation of candidate drugs. Our unique approach integrates iterative big data/in silico and experimental screens, offering the most efficient matching of clinical indications and compound/drug effects. Our R&D process allows a fast track to clinical stage testing; our methodological core is tailored toward precision to increase the probability of success. Our focus is the repositioning of existing drugs for novel indications.
With generating IP for such drug-disease combinations we establish a pipeline of clinically and economically attractive indications. Results of our lead program on the rare chronic kidney disease focal segmental glomerulosclerosis have been published recently (Transl Res. 2023 259:28-34 ; Kidney Int Rep. 2023 9(2):478-481). Previous computational data integration workflows have led to the identification of novel drug combinations in other tumor entities (Oncotarget. 2018 9(91):36379-36391; PLoS One. 2019 14(1):e0210859).
RESPONSIBILITIES
Objectives of the PhD:
The overall objective of this PhD-project in PROMOTE is to consolidate omics profiles in the context of prostate cancer to generate network-based molecular models for the disease. Network alignment methods shall be used to identify compounds that show beneficial interference between disease pathobiology and drug mechanism of action. A particular focus will be placed on compounds that affect target molecules involved in synthetic lethal interactions within the context of tumor progression. The potential of identified compounds and compound combinations targeting synthetic lethal interactions will be tested in combinations with researchers from the Medical University of Innsbruck.
Methods:
The PhD student will mostly work on data analysis and statistical analysis using R or Python. There will be some interaction with the wet laboratory (in-vitro compounds testing).
Expected Results:
- Meta analysis of omics data in the context of prostate cancer
- Generation of a network-based molecular model of prostate cancer
- Identification of compounds interfering with prostate cancer pathobiology
- Identification of drug combinations that address synthetic lethal interactions
REQUIREMENTS
- You hold a master's degree in bioinformatics/computational biology
- Fluent in a scripting language (R or Python) for data wrangling, explorative analysis and data visualization
- A solid understanding of cellular and molecular biology; knowledge of the hallmarks of cancer is a plus (Cell 2000 100:57-70; Cell 2011 144:P646-674)
- Experience with SQL, JSON, XML
- Statistical analysis of large biological datasets (e.g. Omics data)
- Experience with extracting data from key biological databases (NCBI, Ensembl, UniProt, GEO, ArrayExpress)
- Knowledge of key biological ontologies/vocabularies (Medical Subject Headings, Gene Ontology, Anatomical Therapeutic Chemical Classification, ...)
- Knowledge of graph theory and key graph measures
- Experience with biological network modelling and visualization (e.g. Cytoscape, igraph, ...)
Marie Skłodowska-Curie ITN rules:
- You must **NOT** have a **doctoral degree** at the date of your recruitment
- You must comply with the **mobility rule**: **not have resided** or carried out your main activity (work, studies, etc.) **in Austria** for more than 12 months in the 36 months immediately before the recruitment date.
The position includes 2 mandatory stays in partner laboratories to complete training:
1) Mosaiques Diagnostics GmbH: training proteomics data analysis.
2) Medical University Innsbruck: testing of drug combinations derived from the analysis of synthetic lethal interactions.
BENEFITS
- You will benefit from all Marie Skłodowska-Curie Action scheme advantages.
- Participation in web seminars (in English) of the collaborative network of the laboratory.
- Participation in yearly meetings organised by the PROMOTE consortium, as well as international and national congresses.
- You will work at a modern office in the beautiful 8th district of Vienna.
TERMS
3-year PhD position
LOCATION
Vienna / AUSTRIA
COMPENSATION
3.200 - 4.000 EUR brutto / month
HOW TO APPLY
Please submit your candidacy via Join (https://join.com/companies/delta4/11804151) including the following information:
- Your CV and motivation letter
- Your MSc transcript (diploma, courses, and grades)
- Two reference letters or contact details from your previous scientific supervisors
DEADLINE
August 20th, 2024
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BACKGROUND
PhD position: Deciphering molecular mechanisms of acute kidney injury (AKI) to chronic kidney disease(CKD) transition – identification of biomarkers and potential druggable targets
This is a 3-year PhD position, that is part of a European Doctoral Network (DN) program entitled "PersonalIzed medicine in Chronic KidnEy Disease (PICKED)" involving 10 research centres from France, Austria, Spain, Greece, Germany, Denmark, and Estonia.
The PhD position is hosted at Delta 4 GmbH, Vienna, Austria.
Delta4 is a Vienna-based TechBio company at the forefront of digital drug discovery and development. Delta4 leverages a proprietary computational analytics platform (Hyper-C), combined with biomedical testing and clinical validation of candidate drugs. Our unique approach integrates iterative big data/in silico and experimental screens, offering the most efficient matching of clinical indications and compound/drug effects. Our R&D process allows a fast track to clinical stage testing; our methodological core is tailored toward precision to increase the probability of success. Our focus is the repositioning of existing drugs for novel indications. With generating IP for such drug-disease combinations we establish a pipeline of clinically and economically attractive indications. Results of our lead program on the rare chronic kidney diseasefocal segmental glomerulosclerosis have been published recently (Transl Res. 2023 259:28-34; KidneyInt Rep. 2023 9(2):478-481).
The PICKED Consortium / Background:
Kidney diseases both chronic (CKD) and acute (AKI) should be considered as a priority, but also a challenge, for Public Health Policies as they concern >850 million persons in the world. The major urgent needs that have been identified over the last years include i) early detection in "at-risk" patients of CKD, ii) detection and prediction of CKD progression/complications, and iii) personalized treatment avoiding over- or unnecessary treatment, which collectively contributes to the adoption of Personalized Medicine (PM) in CKD.
To address such ambitious challenges, it is essential to train professionals to identify these issues. Constituting a network of 10 PhD students, 6 public laboratories, 4 research and development companies, and several associated partners, the PICKED consortium will work on different aspects of PM aiming to significantly reduce the burden of CKD including: early detection of CKD and its progression; personalized drug and dialysis treatment and the social-economic impact of PM in CKD.
RESPONSIBILITIES
Objectives of the PhD:
The overall objective of this PhD-project in PICKED is to consolidate AKI and CKD omics profiles and generate network-based molecular models for the two disease entities. Network alignment methods shall be used to identify overlapping/interacting molecular mechanisms at the AKI-to-CKD transition. Key molecules of the identified molecular processes will be evaluated regarding their potential to serve as AKI-to-CKD biomarkers or drug targets taking into account information on tissue-specific expression, subcellular location, evidence in scientific literature, and mechanistic role in the context of dysregulated molecular processes. The prognostic potential of selected biomarkers will be evaluated in collaboration with the research group from Inserm, Toulouse.
Methods:
The PhD student will mostly work on data analysis and statistical analysis using R or Python. There will be some interaction with the wet laboratory (mass spectrometry, ELISAs).
Expected Results:
- Generation of the molecular landscape of the AKI-to-CKD transition
- Identification of biomarker candidates linked to relevant AKI-to-CKD mechanisms
- Identification of novel drug targets being linked to AKI-to-CKD pathobiology
REQUIREMENTS
- You hold a master's degree in bioinformatics/computational biology.
- Fluent in a scripting language (R or Python) for data wrangling, explorative analysis and data visualization
- A solid understanding of cellular and molecular biology
- Experience with SQL, JSON, XML
- Statistical analysis of large biological datasets (e.g. Omics data)
- Experience with extracting data from key biological databases (NCBI, Ensembl, UniProt, GEO, ArrayExpress)
- Knowledge of key biological ontologies/vocabularies (Medical Subject Headings, Gene Ontology, Anatomical Therapeutic Chemical Classification, ...)
- Knowledge of graph theory and key graph measures
- Experience with biological network modelling and visualization (e.g. Cytoscape, igraph, ...)
Marie Skłodowska-Curie ITN rules:
- You must NOT have a doctoral degree at the date of your recruitment.
- You must comply with the mobility rule: not have resided or carried out your main activity (work, studies, etc.) in Austria for more than 12 months in the 36 months immediately before the recruitment date.
BENEFITS
- You will benefit from all Marie Skłodowska-Curie Action scheme advantages.
- Participation in web seminars (in English) of the collaborative network of the laboratory.
- Participation in meetings organised by the PICKED consortium, as well as international and national congresses.
- You will work at a modern office in the beautiful 8th district of Vienna.
LOCATION
Vienna / AUSTRIA
COMPENSATION
3.200 - 4.000 EUR brutto / month
HOW TO APPLY
Please submit your candidacy via Join (https://join.com/companies/delta4/11777067) including the following information:
- Your CV and motivation letter
- Your MSc transcript (diploma, courses, and grades)
- Two reference letters or contact details from your previous scientific supervisors
DEADLINE
August 31st, 2024
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BACKGROUND
SPARK, launched by the Simons Foundation in 2016, is the largest study of autism ever undertaken. It is open to all individuals living in the U.S. with a professional diagnosis of autism and their family members. The initiative aims to improve the lives of people with autism by identifying the causes of autism and informing more effective therapies, treatments, services, and supports. Participants share medical and behavioral information through online surveys. They can also choose to provide saliva samples for DNA analysis. This data is made available to researchers worldwide to explore the genetic underpinnings of autism, identify potential subtypes, and power downstream research. SPARK also engages the autism community by offering participants access to the latest research findings and potential opportunities to participate in additional studies.
POSITION SUMMARY
The Bioinformatics team at the Simons Foundation is seeking a full-time senior bioinformatics engineer. The position will play an integral role in returning genetic results to thousands of SPARK participants, including ASD and secondary health-related variants, as well as work with petabytes of genomics data and develop workflows for a variety of informatics needs across SFARI. The ideal candidate will have experience developing bioinformatics pipelines, coding using software development best practices, and performing reproducible genetic analyses.
The candidate will be responsible for bioinformatics analysis of the SPARK return of genetic results process, including tracking samples from sequencing to return, developing and running analysis workflows, and working with the SPARK return of results (RoR) team on the review and selection of returnable variants. The candidate will also be responsible for packaging SFARI cohort genetic datasets for release in SFARI Base as new sequencing data is received and as other dataset updates are needed.
The senior bioinformatics engineer will report to the Deputy Director of Bioinformatics and will work alongside a growing team, including a software engineer, a data manager, and a data analyst on the Bioinformatics team, as well as with Informatics' engineering team, the SDBR (SFARI Data and Biospecimen Repository) team, and various SFARI cohort teams (SPARK, Searchlight, ABN, etc.).
This is a full-time position based at the Simons Foundation offices in New York City.
ESSENTIAL FUNCTIONS & RESPONSIBILITIES
Return of Genetic Results:
- Manage the bioinformatics portion of the return of genetic results process, including delivery of sequencing data, variant analysis, and clinical validation orders
- Track data deliveries of samples sent for sequencing
- Run quality control pipeline to confirm RoR eligibility
- Run variant filtering and annotation pipelines for SNVs/Indels & CNVs
- Coordinate lab confirmation orders for predicted pathogenic variants
- Analyze and summarize statistics for sequencing batches
- Respond to questions from SPARK or lab related to variant predictions/orders
Maintenance and Development of Bioinformatics Pipelines:
- Implement new features in existing pipelines, as needed
- Design, develop, and test new bioinformatics pipelines, implementing end-to-end workflows that integrate existing tools, to support the needs and goals of SFARI and Informatics
Data Releases:
- Package SFARI cohort genomics datasets for release by performing quality control, integrating data from various sources/versions, and documenting datasets details and methods descriptions
- Answer questions about genomics datasets for data in SFARI Base
MINIMUM QUALIFICATIONS
Education:
- Ph.D. in bioinformatics, computational biology, or related field
Required Skills & Experience:
- At least 4+ years of relevant work experience
- Strong Python skills and software development best practices
- Experience with sequencing data (whole exome or whole genome) and related tools
- Experience performing reproducible data analysis
- Experience working in an HPC environment
- Experience with git/github
- Effective oral and written communicator
- Ability to thrive in collaborative environments
Helpful Skills:
- Project management experience
- Experience analyzing large research datasets (>10,000 individuals)
- Familiarity with core genetics concepts
- Solid understanding of statistical analysis
- Experience generating interactive data visualizations or dashboards
- Desire to continually learn and stay up-to-date with best practices and the latest methods
COMPENSATION & BENEFITS
- The full-time annual compensation range for this position is $150,000 – $175,000, depending on experience.
- In addition to competitive salaries, the Simons Foundation provides employees with an outstanding benefits package.
HOW TO APPLY
Required Application Materials:
- Resume / CV
- Cover Letter
- Example code or repositories (e.g., github)
To apply, visit: https://apptrkr.com/5352418
POLICY
The Simons Foundation's Diversity Commitment:
Many of the greatest ideas and discoveries come from a diverse mix of minds, backgrounds and experiences, and we are committed to cultivating an inclusive work environment. The Simons Foundation actively seeks a diverse applicant pool and encourages candidates of all backgrounds to apply. We provide equal opportunities to all employees and applicants for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, genetic disposition, neurodiversity, disability, veteran status, or any other protected category under federal, state and local law.
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DESCRIPTION
Your tasks:
- Creation of genome-relevant databases and international networking
- Creation of scripts and evaluations
- Upgrade and maintenance of server applications and operating systems developed by you
- Installation, configuration and maintenance of clients and servers
- Troubleshooting
Your profile:
- Interest in genetics, especially human genetics, molecular genetics
- Completed technical training with a focus on IT (HTL, IT college, FH or university degree in (bio)informatics)
- Or completed training in the natural sciences (biology or similar university degree) with a special interest in IT solutions
- Knowledge of programming and working with cloud applications
- Experience with databases and programming is an advantage
- Good knowledge of Linux, Shell, Windows
- Solution-oriented, structured and independent work, analytical thinking, pronounced quality awareness, willingness to undergo further training, team spirit
What we offer:
- A challenging and varied area of responsibility
- An appreciative working atmosphere
- Attractive social benefits and further training opportunities
- Flexible working hours, home office possible on a daily basis
COMPENSATION
The minimum gross monthly salary according to the collective agreement is currently € 3800 per month (minimum annual salary €53.200,00). Overpayment is possible depending on qualifications and professional experience.
HOW TO APPLY
Please send your application with the usual documents to the:
Center for Medical Genetics Innsbruck
Prof. Dr. med. Johannes ZSCHOCKE, Ph.D.
Peter-Mayr-Str. 1, A-6020 Innsbruck, Austria
Email: humgen[at]i-med.ac.at
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BACKGROUND
Advancements in single-cell genomic methods are transforming our understanding of biology. We are seeking exceptional students and graduates to work on the challenges and applications of these groundbreaking technologies, especially in the context of cancer immunology and immuno-modulation.
Whether your degree is in Biomedical Sciences, Biochemistry, Molecular and Cellular Biology, Bioinformatics, Computer Science, or Mathematics, if you are passionate about working at the intersection of biology and computation, interested in genomics and thrive in a highly collaborative and dynamic environment, this could be the perfect PhD or PostDoc fellowship for you.
We currently have openings for qualified doctoral (PhD students) and postdoctoral candidates in both computational and wet lab positions. To apply, please send your cover letter, CV, and contact information for at least two references to Dr. Marmar Moussa, Principal Investigator (marmar.moussa[at]ou.edu).
RESPONSIBILITIES
You will conduct original research in one of the following areas:
- Machine/Deep Learning and Data Analytics,
- High Throughput Sequencing and Bioinformatics,
- Computational Genomics,
- Computational Biology, and
- Systems Immunology, or similar fields.
PhD student responsibilities will follow the universities' policies and procedures as customary for PhD students and candidates in an R1 high research activity university.
REQUIREMENTS
- A degree in Computer Science, Computational Biology, Bioinformatics, Biomedical Sciences, or any relevant discipline.
- Basic experience conducting research.
- Experience in bioinformatics pipelines or analysis of sequencing data, such as RNA-seq or ATAC-seq or other is advantageous.
- Expertise in machine learning methods, statistical methods and algorithm development in the context of biological systems is also advantageous.
- Proficiency in R. Knowledge of Python, as well as general proficiency with UNIX operating systems is strongly desired.
COMPENSATION
Our lab has competitive above national average support for PhD and PostDoc positions and projects.
HOW TO APPLY
Contact: Dr. Marmar Moussa
Email: marmar.moussa[at]ou.edu
DEADLINE
We are recruiting PhD students for 2024 and 2025 academic years' semesters.
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SUMMARY
This is a Lead Computational Biologist position in the Bioinformatics Shared Resources. The staff member provide bioinformatics support for complex research projects involving multidisciplinary teamwork and collaboration, and supply support to the Scientific Director that this position reports to. The Lead Computational Biologist must have a broad understanding of key biological concepts and knowledge enabling an integrated understanding of biological data analysis as it relates to underlying biological processes. The individual can bidirectionally communicate with biologists with clarity and understanding, and then translate client objectives into approaches involving a variety of computational methodologies. In addition to the basic computational competencies, the individual will play an important role advising clients on experimental design, and coordinating with other group members on data analysis, in particular NGS sequencing data analysis and integration of multi-omics data analysis.
RESPONSIBILITIES
- Collaborate closely with researchers to understand research objectives, suggest appropriate statistical designs consistent with meeting those goals, communicate analysis results, and facilitate interdisciplinary collaborations. Present findings at meetings, seminars, and conferences.
- Conduct comprehensive analyses of biological data generated by researchers, including genomic, transcriptomic, epigenetic, proteomic, and metabolomic datasets. Interpret results and provide insights to researchers to support their research goals.
- Develop, optimize, and maintain bioinformatics pipelines and workflows for processing and analyzing high-throughput sequencing data and other biological data types. Ensure pipelines are scalable, reproducible, and aligned with best practices. Keep abreast of emerging technologies, methodologies, and resources to enhance the capabilities of the Bioinformatics Core.
- Provide training, workshops, and educational resources to researchers on bioinformatics tools, methodologies, and data analysis techniques. Foster a culture of computational literacy and empower researchers to leverage bioinformatics resources effectively.
- Document analysis workflows, methodologies, and results in clear and complete manner.
- Participates in publication and presentation of research
- Coordinates and cooperatively manage resources (servers, data storage, and internet connectivity) with IT staff
- Performs other duties as required or assigned which are reasonably within the scope of the duties in this job classification
- Understands and performs in accordance with all applicable regulatory and compliance requirements
- Complies with all standard operating policies and procedures
QUALIFICATIONS
Education:
- PhD in bioinformatics or related field required
Experience:
- More than 2 years of relevant experience preferred, however newly graduated PhD's are also encouraged to apply.
- Experience with the analysis and interpretation of single cell datasets preferred
- Experience working in a bioinformatics core facility or shared resource environment, providing bioinformatics support and services to researchers
LOCATION
Milwaukee, WI, USA
COMPENSATION
Based on experience
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BACKGROUND
At Eisai, satisfying unmet medical needs and increasing the benefits healthcare provides to patients, their families, and caregivers is Eisai's human health care (hhc) mission. We're a growing pharmaceutical company that is breaking through in neurology and oncology, with a strong emphasis on research and development. Our history includes the development of many innovative medicines, notably the discovery of the world's most widely-used treatment for Alzheimer's disease. As we continue to expand, we are seeking highly-motivated individuals who want to work in a fast-paced environment and make a difference. If this is your profile, we want to hear from you.
Translational Discovery group in Human Biology Integration covers oncology preclinical and clinical translational research to accelerate clinical development of candidate drugs and to enable identification of novel targets. Data science, computational biology and bioinformatics are a fundamentally important core discipline and integral part of the Translational Discovery group. Data scientists play a key role in leveraging internal and external cancer genomics and pharmacogenomics data for developing new breakthrough oncology drugs, with a sharp strategic focus on employing entrepreneurial collaborative and business models to accelerate delivery of innovative medicines that address unmet patient needs.
SUMMARY
We are seeking a highly motivated data scientist to join the Translational Discovery group. This person will be responsible for performing hands-on exploratory and regulatory related biomarker analysis, large-scale genetic, genomic, and other 'omic analyses, with a primary goal of identifying and validating targets and biomarkers in preclinical studies and clinical trials for oncology. More specifically, this person will participate the design of genomic studies in preclinical and clinical research, implement cutting-edge informatics and statistical methods and tools to analyze the data including WGS/WES/targeted sequencing, RNAseq, proteomics data, metabolomics data, etc, and perform integrative analysis of genomic data and available clinical data in clinical trials. Furthermore, the individual will leverage external cancer genomic and pharmacogenomics data, and oncology real-world data (RWD) to integrate with Eisai internal data for biomarker analysis. All analysis work will be documented and will follow best practices for enabling reproducible research.
PRINCIPAL DUTIES & RESPONSIBILITIES
- Perform data analysis activities including cleaning, handling, integration, and analysis of biomarker data generated in clinical trials, including WES, RNA sequencing, serum proteins, and other data types to identify biomarkers correlated with clinical endpoints.
- Perform data analysis activities integrating internal and external multi-scale data generated from cell lines, model organisms, and human subjects, including genetic, genomic data, functional data, phenotypic data, and RWD to inform novel targets, combination strategies, or novel cancer indications for oncology assets that are currently under development.
- Analyze large-scale analysis-ready datasets to answer specific focused questions of relevance to project teams.
- Provide appropriate visualization and interpretation of results in preclinical and clinical data to support decision making on drug development projects.
- Contribute to clinical biomarker study design to generate statistically meaningful information.
- Contextualize findings from internal experiments and generate hypotheses for new internal experiments by analyzing and interpreting externally available data.
- Prepare and track documentation including analysis plans, result reports, and progress reports.
REQUIREMENTS
- Ph.D. degree in Biomedical Sciences, Bioinformatics, Computational Biology, or closely related field. 2-5 years of post-graduate experience in hands-on cancer genomic data analysis.
- Must have analytic and statistical skills to conduct analysis of WGS/WES, transcriptomic, proteomic and epigenetic data. Must have experience in oncology clinical outcome analysis.
- Must have a good understanding of human biology. Experience in cancer research is highly desirable. Must demonstrate good understanding of drug discovery requirements and processes.
- Must have strong organizational skills and ability to prioritize work.
- Must have excellent communication skills and the ability to act on cross-disciplinary teams; must have demonstrated ability in scientific publications.
- Must have experience with R, Unix/Linux systems and AWS cloud computing. Additional experience with languages/software including Python, SQL, Spotfire is strongly preferred.
POLICY
Eisai is an equal opportunity employer and as such, is committed in policy and in practice to recruit, hire, train, and promote in all job qualifications without regard to race, color, religion, gender, age, national origin, citizenship status, marital status, sexual orientation, gender identity, disability or veteran status. Similarly, considering the need for reasonable accommodations, Eisai prohibits discrimination against persons because of disability, including disabled veterans.
Eisai Inc. participates in E-Verify. E-Verify is an Internet based system operated by the Department of Homeland Security in partnership with the Social Security Administration that allows participating employers to electronically verify the employment eligibility of all new hires in the United States. Please click on the following link for more information:
Right To Work (https://us.eisai.com/-/media/Files/Eisai/RightToWorkPoster.pdf?la=en)
E-Verify Participation (https://us.eisai.com/-/media/Files/Eisai/EVerifyParticipationPoster.pdf?la=en)
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DESCRIPTION
Join Our Team at Dr. Gu's Lab, Versiti Blood Research Institute, Milwaukee, WI.
Are you a driven and passionate individual with expertise in machine learning, bioinformatics, biostatistics, genomics, genetics, computational biology, or cancer biology? If so, we invite you to become part of our dynamic team at Dr. Gu's lab at the Versiti Blood Research Institute in Milwaukee, WI. We are seeking a highly motivated Postdoctoral Fellow to contribute to groundbreaking research in the field of multi-omics data analysis, cancer biology, and biomarker discovery.
Position Overview:
As a Postdoctoral Fellow, you will have the unique opportunity to develop and implement cutting-edge machine learning algorithms and statistical models. These tools will be applied to unravel the complexities of multi-omics data, shedding light on the mechanisms underlying cancer biology (leukemia, lung, and kidney cancer) and facilitating the identification of early diagnostic and treatment biomarkers. Additionally, if you have an interest in experimental work, you will have the chance to gain valuable hands-on experience and training.
REQUIREMENTS
Education:
- Master's Degree required
- PhD required
- Equivalent degree required
Experience:
- 0-6 years of postdoctoral training required
- Proficiency in Python or R, ideally both
- Knowledge of biology, genomics, genetics, and Next Generation Sequencing data is a valuable asset.
WHY JOIN US
- Contribute to cutting-edge research in a collaborative and innovative environment.
- Access state-of-the-art resources and mentorship to support your career development.
- Work in a vibrant city with a rich cultural scene and a welcoming community.
HOW TO APPLY
If you are passionate about harnessing the power of data to advance our understanding of cancer biology and want to be part of a team dedicated to making a difference, we encourage you to apply.
To apply for this position, please submit your CV, a cover letter detailing your research interests and relevant experience and contact information for at least three references to tgu[at]versiti.org.
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BACKGROUND
GDIT is seeking an experienced Scientific Program Manager to lead our Scientific IT program, supporting a large biomedical research community for our customer with the National Institute of Allergy and Infectious Diseases (NIAID).
Our Scientific IT program is responsible for enabling High Performance Computing and its associated infrastructure across multiple locations, scientific applications and instrumentation, and ~40PB of data storage to include data archive and sharing services. This program serves as a customer-facing presence for the NIAID research community, providing a single point of support for new initiatives, ongoing projects, and scientific IT needs. In your role as a Scientific Program Manager, you will lead a multidisciplinary team responsible for delivering comprehensive scientific services to an end-user community of approximately 4500.
Under your leadership, you will be responsible for developing and implementing customer support policies and procedures with a focus on metrics driven execution to ensure that scientific and computational services are delivered to our client on time and efficiently. You will proactively identify areas for improvement, implement process enhancements, and drive efficiency for our scientific services portfolio. You will prioritize building relationships with researchers to understand their needs, solve challenges, and align our program to deliver value to support scientific research. You must be able to simultaneously manage various duties and obligations such as project and team management to ensure customer satisfaction while enhancing the caliber of services delivered.
RESPONSIBILITIES
- Provides day to day team management and oversight of project execution and service delivery for scientific infrastructure and scientific instrumentation teams. This includes delegating tasks, providing clear direction, and inspiring collaboration and teamwork.
- Accountable for the development and delivery of scientific IT services and capabilities, strategic planning, budgeting and forecasting, and customer outreach and engagement.
- Overseeing personnel management including staff recruitment, hiring, performance management, training, and mentoring.
- Ensures service delivery alignment with program and customer strategic goals by developing strategic roadmaps and tracking KPI's.
- Collaborates with internal and external resources to identify new service offerings to enable and advance scientific research. Develop plans and identifies resources required for implementation and execution.
- Facilitate regular discussions with researchers to understand needs and challenges.
- Provides transparent communications on project timelines, resource requirements, risk management, and status reporting across all organizational and technical boundaries.
- Provides oversight for critical incidents, coordinating with resolution parties and establishing effective communication between stakeholders for post incident reviews and after-action reporting.
REQUIREMENTS
- Masters and 5+ years experience or equivalent in a Science and IT related discipline
- 5+ years experience leading multiple computational science programs
- 5+ years experience in IT project management or development and delivery of scientific IT services
- Demonstrated experience leading multidisciplinary teams supporting operations and maintenance of computational science systems and applications
- Understanding of general workflows for scientific data generation, analysis, and reporting
- Understanding of challenges and approaches for large scale scientific data management
- Experience developing and aligning relationships with diverse stakeholders at all levels from scientists through senior leadership
- Experience providing accurate and regular reports to measure how deliverables align with the organization values and strategic objectives
PREFERENCES
- Education or experience in life or physical sciences
- Experience leading cross-functional teams including scientists and engineers
- Experience leading teams supporting engineering and administration of computational science infrastructure, including HPC and associated components
- Experience providing IT support for scientific instrumentation installation, configuration, operations, and troubleshooting
- Experience supporting large collections (hundreds) of shared applications, many of which are open source
- Familiarity with genomic analyses tools, workflows and data types
- Familiarity with Agile Scrum and/or Kanban methodologies
- Familiarity with principles and practices of ITIL to include incident management, problem management, service request management, change management, and service level management.
- Understanding of the National Institute of Standards and Technology (NIST) cybersecurity framework and Security Assessment and Authorization (SA&A) process
LOCATION
This position is primarily remote; however, you must reside within commuting distance to the client site in Rockville, MD and be able to be onsite at least 1x a week to meet contractual obligations and project needs. Possible travel to the Montana location.
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BACKGROUND
The Center for Biosustainability (CFB) at DTU (Denmark) and the FEMSA Biotechnology Center (CBF) at Tecnológico (TEC) de Monterrey (Mexico) have launched a joint research program to foster a bilateral strategic partnership to promote innovative projects in biosustainability (Joint CFB-CBF research program).
The Computational Protein Engineering (CPE) group at DTU Biosustain and the Molecular and Systems Bioengineering (MSB) group at TEC campus Guadalajara (Jalisco) are offering one postdoctoral position as part of this Joint CFB-CBF program in the area of in vivo enzyme evolution in yeast for C1 metabolism. The candidate will be hired at DTU but It is required that the candidate makes at least a six month stay in the Tecnológico de Monterrey Campus Jalisco, Mexico.
RESPONSIBILITIES & QUALIFICATIONS
We are looking for a colleague who is independent, will thrive within an interdisciplinary environment at two world-class research centres in Denmark and Mexico (short-term research visit at TEC for 6 months), and is highly motivated to develop novel biosustainable solutions using cutting-edge research approaches.
Responsibilities:
- Engineer yeast strains to assimilate C1 feedstocks.
- Perform genome mining to identify enzyme candidates using bioinformatic approaches.
- Characterize enzyme variants using biophysical and biochemical methods.
- Generate and analyze large enzyme mutant datasets using in vivo directed evolution tools and next-generation sequencing.
- Implement adaptive laboratory evolution (ALE) campaigns using automation.
- Report your research results in peer-review scientific publications and international conferences.
- Collaborate within the CPE and MSB research groups and across DTU and TEC network.
Qualifications:
- PhD in biotechnology, biochemistry, biology, chemistry, biophysics, or related area.
- Experience with yeast genetics, molecular biology, and bioinformatics.
- Basic programming skills in Python or similar languages.
- Excellent written and oral English proficiency.
- Excellent communication skills for working within an interdisciplinary research team.
- Strong analytical skills and ability to work independently.
Preferred qualifications (not mandatory):
- A strong publication record in peer-review scientific journals.
- Experience with grant and patent writing as well as teaching.
- Experience with protein and metabolic engineering.
- Experience with directed evolution and adaptive laboratory evolution (ALE).
- Interest in learning automation, robotics, and machine learning to improve protein function.
- Interest in entrepreneurship to make a positive impact on planetary and human health.
WE OFFER
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.
Salary & terms of employment:
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.
The period of employment is 2 years. The preferred starting date is July 1st, 2024, or according to our mutual agreement. The position is full time.
You can read more about career paths at DTU here: https://www.dtu.dk/english/about/job-and-career/working-at-dtu/career-paths
HOW TO APPLY
Your complete online application must be submitted no later than 5 May 2024 (23:59 Danish time).
Apply at: Postdoc in Directed Enzyme Evolution of C1 metabolism: https://efzu.fa.em2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/3381/?utm_medium=jobshare
Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:
- Application (cover letter)
- CV
- Academic Diplomas (MSc/PhD – in English)
- List of publications
Applications received after the deadline will not be considered.
All interested candidates irrespective of age, gender, disability, race, religion, or ethnic background are encouraged to apply.
ABOUT US
DTU Biosustain is an interdisciplinary research center that develops new knowledge and technology to support the production of biochemicals, natural products and microbial foods using fermentation processes based on microbial hosts or enzymatic processes.
Technology for people:
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN's 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.
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BACKGROUND
Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington.
With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world's leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world's deadliest diseases and make life beyond cancer a reality.
At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. These values are grounded in and expressed through the principles of diversity, equity and inclusion. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems. Fred Hutch is in pursuit of becoming an anti-racist organization. We are committed to ensuring that all candidates hired share our commitment to diversity, anti-racism and inclusion.
The Chief Data Officer of the Fred Hutchinson Cancer Center, Jeff Leek, established the Fred Hutch Data Science Lab (DaSL) to develop and support the overall data strategy for the organization. The mission of the Data Science Lab is to ensure an effective data ecosystem at Fred Hutch by developing a modern, well documented, well implemented, overall data strategy. This should serve the needs and capabilities of those leveraging data at Fred Hutch regardless of "where they live" from the clinic to the research groups. We believe focusing on people is critical in building a strong, dynamic community united around using data to improve human health and cancer care. To do this, we aim to build a diverse, hybrid team that is inclusive, open, collaborative, and supportive both within our team and with our collaborators (find more about our values and culture). We are strong advocates for open science and reproducible research, thus develop our work in the open as much as possible. We rely heavily on written communication and continuous collaboration in order to support our hybrid team, as well as make our work as accessible as scalably and sustainably as possible by Fred Hutch staff.
This position will work with colleagues within the Data Science Lab and across the institution to develop a training program to meet the data science needs of Fred Hutch researchers. This includes working with a diverse population of scientists and administrators to build a community of data science learners at all levels, as well as creating, adapting, and delivering training materials and resources to meet the diverse data-related training needs of the Fred Hutch community and the diverse ways in which people prefer to learn. As such, the Director of Training and Community has a background in health and biomedical data science and must be enthusiastic about collaborating with others, creating a system for developing and delivering open-source training, and furthering the success of the Fred Hutch community.
This role will have the opportunity to work partially at our campus and remotely.
This position is eligible for a sign on bonus and relocation.
RESPONSIBILITIES
- Work with the Chief Data Officer, Deputy Chief Data Officer, other DaSL leadership, and training staff to create a comprehensive data science training program for the Fred Hutchinson Cancer Center, based on needs assessment and input from on-going data science house calls.
- Collaborate with Fred Hutch researchers to identify further training needs and translate into expanding the training program, including performing surveys of needs of the Hutch community.
- Prioritize training development and delivery plans to meet the Fred Hutch community needs.
- Develop a strategy for delivering this training program in a modern, flexible format to meet the needs of providers, researchers, administrators, and the Fred Hutch community broadly.
- Strategize training delivery across different modalities (courses, workshops, videos, etc.) and platforms (website, coursera, etc.) to enhance audience reach.
- Develop a model structure for courses by leveraging open source technologies and adopting an approach to open, collaborative course development.
- Coordinate efforts with the Fred Hutch Office of Education and Training (OET) and other training groups at Fred Hutch.
- Host/lead online and in-person courses, presentations, and sessions about change management to support the evolving data culture at Fred Hutch.
- Supervise and mentor Fred Hutch funded training staff.
- Collaborate with the grant-funded staff to create a cohesive experience across all training efforts regardless of funding source.
- Supervise training curricula and implementation in Fred Hutch training-related efforts.
- Strategize in close collaboration with PIs of grant-funded projects to reuse/adaption of materials to maximize use of data science education materials.
- Contribute to building community by interacting with various groups at Fred Hutch.
- Recruit training team members and larger Fred Hutch community members to contribute to and review sections of the FH Biomedical Data Science Wiki. Manage review of these contributions.
- Work with other DaSL domain experts to lead DaSL Community Studios program (coworking groups on particular topics).
- Evaluate how well the training program is meeting Fred Hutch community needs through analytics and evaluations.
REQUIREMENTS
- MD, PhD (or equivalent), or Masters in Bioinformatics, Statistics, Biostatistics, Mathematics, Computer Science, Data Science, or related field required.
- Years of experience: 4 years of experience in combination of data science and/or training, at least one year in each.
PREFERENCES
- Strong experience with public speaking, including both online and in-person presence.
- Developed and taught courses in data science, biostatistics, data analysis, artificial intelligence, or related fields.
- Core competency in at least one of the following: genomics, natural language processing, image processing, clinical data analysis, machine learning/artificial intelligence, computational biology, biostatistics.
- Proficiency in R and or Python (or equivalent) and version control with Git/GitHub (or equivalent)
- Experience with managing a group of people and prioritizing tasks.
- Passion for democratizing data science and computational biology skills.
- Developed or assisted in developing and leading a data program that included training/education components in either an academic, professional development, or technical environment.
- Experience with DEI, classroom safety, working with diverse populations in an educational setting.
- Experience with community building techniques.
- Experience or interest in pedagogical research.
- Experience with HTML, CSS, high performance computing, Cloud platforms, containers, SQL, markup languages.
COMPENSATION
The annual base salary range for this position is from $120,869 to $191,027, and pay offered will be based on experience and qualifications.
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DESCRIPTION
Interested in bioinformatics, eDNA metabarcoding, and want to work in Hawaii?
Join the Cooperative Institute for Marine and Atmospheric Research (CIMAR) at NOAA's Pacific Islands Fisheries Science Center (PIFSC) and the National Marine Fisheries Service (NMFS) 'Omics Network as a Bioinformatics Assistant Researcher. Contribute to improving the analytical workflows needed to operationalize environmental DNA (eDNA) metabarcoding surveys to enhance biodiversity exploration and monitoring across marine ecosystems from coral reefs to the deep-sea. Together with other new hires at NOAA Science Centers across the nation, be a part of the newly established NMFS 'Omics Network designed to collaboratively develop powerful, reproducible, and streamlined end-to-end operational workflows that automate the analysis of eDNA metabarcoding data.
About Us: PIFSC provides science to support the conservation and management of fisheries and living marine resources across the Pacific Ocean. Our group in the Ecosystem Sciences Division has already generated two big 6-assay ecosystem-scale eDNA datasets from both pelagic and coral reef ecosystems in the Hawaiian Islands, each of which offer exciting opportunities to explore new ecological patterns and generate novel biodiversity products.
The Opportunity: We are seeking a Bioinformatics Assistant Researcher (Postdoc/early Career Researcher) to co-lead the improvement of analytical workflows for eDNA metabarcoding in our marine ecosystem surveys. This is a 3-year, full-time position supported by the Inflation Reduction Act, located at NOAA's Inouye Regional Center in Honolulu, Hawaii. Annual Salary range $67,200-$75,600, commensurate with experience. You'll work closely with a collaborative team of researchers to improve data analysis techniques, refine existing resources and/or develop novel tools to build reproducible, flexible, and automated workflows for multi-marker, multi-trophic level eDNA metabarcoding data streams using rich existing datasets.
Opportunities include: Working with two robust datasets, which couple eDNA with classical field survey techniques to deepen our understanding of ecosystem structure and generate novel products in both Pacific coral reef and pelagic ecosystems. Leading and contributing to impactful scientific papers advancing the integration of eDNA with existing surveys. Collaborating with a diverse and inclusive team of researchers at PIFSC, and the broader NMFS 'Omics Network.
Qualifications: We are looking for a highly motivated candidate with a strong background in Bioinformatics and a PhD in Bioinformatics, Molecular Ecology, Data Science, Biology or related field. You should ideally be knowledgeable of current metabarcoding pipelines, have strong programming skills in one or more languages, and be proficient in R. Ideally you will have a background in genomics, community ecology, biodiversity analyses, and data visualization. Knowledge of marine ecology is preferred, but not required. Skillsets and expertise in other systems could be easily applied.
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