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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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BACKGROUND
To strengthen our team in the division "Molecular and Applied Entomology" in Berlin-Steglitz, starting 01.05.2024, we are looking for a
PhD student (m/f/d) in the field of biology, bioinformatics, biochemistry or comparable
Salary group 13 TVöD
Temporary contract for 36 months
The working time is 65%
The Bundesanstalt für Materialforschung und -prüfung (BAM) is a materials research organization in Germany. Our mission is to ensure safety in technology and chemistry. We perform research and testing in materials science, materials engineering and chemistry to improve the safety of products and processes. At BAM we do research that matters. Our work covers a broad array of topics in the focus areas of energy, infrastructure, environment, materials, and analytical sciences.
We are looking for talented people to join us.
RESPONSIBILITIES
Your responsibilities include:
Working on the DFG-funded project "The evolution of symbiont, pathogen and immune system interactions in Blattodea", which has the overarching goal of exploring how symbiont transitions have shaped pathogen defenses and immune systems in Blattodea. The project will involve:
- Identification and testing of immune genes involved in the regulation of symbionts and exploration of how they have evolved
- Tissue-specific transcriptomics in conjunction with microbiota and symbiont manipulation experiments
- Insect field sampling
- Use of available high-quality genomes to characterize immune genes and to better understand evolutionary changes between hosts and their symbionts
- Collaboration with project partners to quantitatively analyze genome, microbiota and pathogen data
- Active contribution to the DFG research group "Insect Infect (FOR 5026)"
- Writing scientific articles for publication in peer-reviewed journals
- Writing a doctoral thesis
- Presentation of project results at international scientific conferences
REQUIREMENTS
Your qualifications:
- Successfully completed scientific university degree (master's degree or equivalent) in the field of biology, bioinformatics, biochemistry or comparable
- Practical experience with insects and microbes
- Very good knowledge and experience in molecular biology
- In-depth knowledge of evolutionary biology and genetics
- Experience in the quantitative and statistical analysis of data with Python, R, or similar
- Knowledge of computer-based analysis of large data sets, especially nucleotide sequences
- Willingness to collaborate across disciplines
- Excellent written and spoken English skills
- Good communication and information processing, goal-oriented and structured way of working, ability to work in a team and willingness to cooperate
COMPENSATION
We offer:
- Interdisciplinary research at the interface of politics, economics and society
- Work in national and international networks with universities, research institutes and industrial companies
- Outstanding facilities and infrastructure
- Flexible working hours and mobile working
HOW TO APPLY
Your application:
We welcome applications via the online application form (https://recruitingapp-5507.de.umantis.com/Vacancies/1837/Application/New/2) by 20.03.2024. Alternatively, you can also send your application by post, quoting the reference number 39/24-4.6 to:
Bundesanstalt für Materialforschung und -prüfung
Referat Z.3 - Personal
Unter den Eichen 87
12205 Berlin
GERMANY
http://www.bam.de
Dr. McMahon will be glad to answer any specific questions you may have. Please get in touch via the telephone number +49 30 8104‑3837 and/or by email to dino-peter.mcmahon[at]bam.de.
POLICY
BAM promotes professional equality between women and men. We therefore particularly welcome applications from women. At the same time, we strive to reflect social diversity. Every application is therefore welcome, regardless of gender, cultural or social background, religion, ideology or sexual identity.
In addition, BAM has set itself the goal of promoting the professional participation of people with severe disabilities. The fulfillment of the job requirements is considered on an individual basis. Severely disabled persons or persons of equal status will be given preferential consideration if they are equally qualified.
The advertised position requires a high level of physical aptitude.
BAM actively supports the compatibility of work and family and has been certified as a family- and life-phase-conscious employer by the "audit berufundfamilie" since 2015.
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BACKGROUND
The Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR) is seeking outstanding faculties in clinical data science research.
The Bioinformatics Institute (BII) is a computational biology research and postgraduate training institute as well as a national resource centre in bioinformatics within the Biomedical Research Council (BMRC) of A*STAR. Our scientists aim to understand the biomolecular mechanisms that underlie biomedical phenomena by developing sophisticated computational methods to support discovery from a secure and sustainable data hub to cross-disciplinary AI/ML analysis and data integration. We analyse a wide spectrum of biological and clinical data, including omics data (biomolecular sequences, expression profiles, epigenetics data), 3D structures of macromolecules, and biological tissue and macroscopic images from local and international academic, hospital and industry collaborators, public resources and also from in-house efforts. The institute has a vibrant and diverse research portfolio that includes infectious diseases, computational toxicology, precision medicine, oncology and drug discovery.
Watch the videos of BII Scientific Conference 2022 to know more about the research by different groups in BII:
https://www.youtube.com/playlist?list=PLcenRySmzqv76JVbdzg3z5kndDHN3FzBk
RESPONSIBILITIES
1. Heading a laboratory specializing in either one of the following:
a. Quantum Computing for biomedical applications
b. Clinical data hub and clinical data analysis
c. AI and generative models in healthcare applications (e.g. synthetic data)
d. AI in drug discovery
2. Collaborate closely with clinicians and with faculties within the Bioinformatics Institute and within the local ecosystem.
3. Collaborate with industrial partners to translate technologies into the clinics.
4. Lead or participate in research grant proposals (~SGD5million to SGD15million quantum).
REQUIREMENTS
- Outstanding research outcomes with strong publication records
- Excellent communication (oral and written) and public speaking skills
- Strong records of strategic thinking ability
COMPENSATION
The salary will commensurate with the experience and expertise.
HOW TO APPLY
Interested applicants please send your application package to Faculty Search committee:
- Maple Ye Maple_Ye[at]bii.a-star.edu.sg
- Sebastian Maurer-Stroh sebastianms[at]bii.a-star.edu.sg
- Lee Hwee Kuan leehk[at]bii.a-star.edu.sg
- Neerja Karnani Neerja_Karnani[at]bii.a-star.edu.sg
- Chandra Verma chandra[at]bii.a-star.edu.sg
Or apply here: https://careers.a-star.edu.sg/jobdetails.aspx?ID=Gtn0gsck%2fAUXA1g380NlGw%3d%3d
Application packages should consist of:
1. Curriculum Vitae which should include a list of publications
2. Research proposal
3. Names and emails of referees
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BACKGROUND
Dr. Zizhang Sheng's lab at Columbia University Irving Medical Center, Department of Medicine, Division of Infectious Diseases, the Aaron Diamond AIDS Research Center (ADARC), applies bioinformatics and biochemical approaches to elucidate the mechanisms of humoral immune response to infection (HIV, SARS-CoV-2, influenza, malaria, etc.) and to understand the role and origin of autoreactive B cells in autoimmunity (systemic lupus erythematosus, IgA nephropathy, etc.).
Sheng Lab details can be found here: https://www.infectiousdiseases.cuimc.columbia.edu/profile/zizhang-sheng-phd
The Sheng Lab pursues scientific research in cutting-edge fields and has published over 80 papers in Cell, Nature, Nature Communications, Cell Reports, etc.
Position Summary: We are seeking a highly motivated and talented individual to join our team as a Bioinformatics Associate Research Scientist. This position offers an exciting opportunity to contribute to cutting-edge research in the field. The position will involve analyzing next-generation sequencing data of single cell transcriptome and antibody repertoire to study affinity maturation mechanisms of pathogen or auto-antigen specific antibodies and disease pathogenesis. In addition to NGS analysis skills, the incumbent with experience on structural bioinformatics, deep-learning, or biochemical assays including protein expression and production, ELISA, SPR are preferred. The incumbent will work closely with a multidisciplinary team of both computational and experimental researchers and gain valuable experience in advanced data analysis techniques, algorithm development, and the interpretation of NGS data.
RESPONSIBILITIES
- Conduct bioinformatics analyses to interpret high-throughput sequencing data, including transcriptomics and antibody repertoire.
- Using structural bioinformatics approaches to study the mechanisms of antibody-antigen interaction, antibody design, and viral escape.
- Collaborate with experimental biologists to design and execute bioinformatics experiments that address key research questions.
- Participate in scientific discussions, present research findings at meetings and/or conferences, and contribute to scientific publications.
- Mentor and assist junior researchers in bioinformatics techniques and data analysis.
REQUIREMENTS
Minimum qualifications:
- Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related field.
- Strong programming skills in languages such as Python, R, or Perl.
- Experience with next-generation sequencing data analysis (e.g., RNA-Seq, antibody repertoire).
- Proficiency in using bioinformatics software and tools (e.g., CellRanger, Seurat, SAMtools, PyMOL, alchemical free energy perturbation, molecular dynamics simulation, deep-learning etc.).
- Knowledge of statistical analysis methods.
- Excellent problem-solving skills and the ability to work both independently and collaboratively.
- Effective communication skills, including the ability to present research findings to diverse audiences.
- A strong publication record and a demonstrated passion for bioinformatics research.
COMPENSATION
$77,000 - $80,000 per year
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