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    Submitter

    SUMMARY

    Encodia is an emerging, early stage biotech company developing the next generation of protein analysis tools. Encodia is seeking to recruit an experienced bioinformatics scientist with extensive experience combining next generation sequence analysis with protein sequence and data analysis. This candidate should have functional expertise in sequence alignment for both protein and DNA sequences, and experienced with analyzing large data sets using cloud platforms. In addition, this individual will be responsible for establishing and managing analysis tools for directed evolution and structure-based optimization data sets, and develop pipelines for automated workflows.

    RESPONSIBILITIES

    • Develop new methods for analyzing next-generation sequencing data.
    • Develop and employ bioinformatics tools for protein modeling, sequence alignment, and quantitation.
    • Develop and manage compute pipelines in production environments.
    • Collaborate across functions to develop tools to enhance data analysis workflows.

    REQUIREMENTS

    • PhD in Bioinformatics or related field with 3-5 years direct experience in NGS and optionally Proteomics
    • Significant experience in hands-on analysis of next-generation sequencing data analysis
    • Develop and maintain statistical analytical tools and bioinformatics pipelines
    • Programming strength in Python/Perl, and R scripting (Bioconductor)
    • Experienced in Unix/Linux environment
    • Self-motivated and ability to work with and support many functions across organization
    • Experience in machine learning and statistical analysis of big data
    • Minimum 2 years experience Experienced with cloud computing including AWS and/or Google Cloud Platform setting-up and maintaining cloud-based computing environment (i.e. AWS, Azure, etc.)
    • Experience with bioinformatics DNA and Protein analysis tools and databases (NCBI, UCSC Genome Browser, IGV, ExPASy tools and databases, homology modeling, DNA and protein sequence alignment algorithms, UniProtKB, SWISS-MODEL, etc.)
    • Use GitHub coding and documentation standards

    COMPENSATION

    Benefits: Encodia is an Equal Opportunity Employer that offers a competitive and comprehensive employee benefits package including medical plans, dental insurance, vision plans, LTD, paid vacation, and a stock plan.

    HOW TO APPLY

    Please apply online at encodia.workable.com for Bioinformatics Scientist position.

    Website: www.encodia.com.

    BACKGROUND

    A post-doctoral position focused on the omics (e.g., genetic, genomic, transcriptomic, epigenomic, etc.) associations with chronic pain is available in the Department of Pain and Translational Symptom Science (PTSS) at the University of Maryland, Baltimore. The PTSS department has a vibrant and collaborative group of pain and symptom scientists who apply cutting edge methods in basic, translational and clinical research. The department is also home to a National Institute for Nursing Research (NINR) P30-funded Omics Associated with Self-Management Interventions for Symptoms (OASIS) Center. In addition, faculty and trainees in the PTSS department are members of the interdisciplinary campus-wide Center to Advance Chronic Pain Research (CACPR). The CACPR hosts bi-weekly pain interest group seminars and annual symposia on a variety of chronic pain topics.

    We seek a motivated post-doctoral fellow with experience and formal training in pain physiology, bioinformatics and the analysis of large omics datasets to join our group. We have a variety of pre-clinical and clinical projects ongoing that are aimed at elucidating the omics associations with the development and persistence of chronic pain in a number of conditions including low back pain, chemotherapy-induced neuropathic pain, spinal cord injury and others.

    The UMSON is part of the University of Maryland graduate professional campus that also includes the schools of medicine, dentistry, social work, pharmacy and law, and is one of the fastest growing biomedical research centers in the nation. The unique composition of the campus enables health professionals to address clinical care, public policy and social issues through inter-professional research, scholarship, teaching and community action. Its location in the Baltimore-Washington, D.C.-Annapolis triangle maximizes opportunities for collaboration with government agencies, health care institutions and life sciences industries.

    RESPONSIBILITIES

    Primary:
    • Research interests aligned with omics associated with chronic pain conditions
    • Substantively contribute to the research and scholarship efforts of the OASIS Center and PTSS department through the dissemination of peer-reviewed, data-based publications.
    • Actively participate in PTSS department and CACPR activities.

    REQUIREMENTS

    Qualifications:
    • Doctoral degree (PhD) in biology, bioinformatics (preferred), nursing or a related field
    • Evidence of scholarly achievement in terms of data-based publications, extramural funding for pre-doctoral research training and participation in regional or national research presentations
    • Eligibility for appointment at the rank of post-doctoral fellow
    Candidates for this position should hold a PhD in biology, bioinformatics, nursing or a related field, have strong motivation to develop an independent research career, and excellent dissemination skills (oral and written).

    HOW TO APPLY

    Search here for job number 1800000Q: umb.taleo.net/care[...]ng=en

    Interested candidates should submit a single PDF document containing a letter of interest, CV, brief personal statement describing research interests and career goals, and contact information for three references.

    BACKGROUND

    Dr. Nicholas Schork, Director of Quantitative Medicine at TGen, seeks a creative, independent, and highly motivated researcher interested in developing and applying novel and comprehensive quantitative methods for understanding and characterizing the genetic and molecular determinants of human longevity and longevity enhancement. Dr. Schork is one of the two principal investigators (PIs) for the NIA-funded longevity consortium, whose goal is to characterize the genetic basis of human longevity, and a co-PI on another NIA-funded consortium grant to identify genetic targets for longevity-enhancing interventions. The methods, analyses, and tools to be developed will leverage these connections, but go beyond them, in developing bioinformatic and biostatical analysis methods to identify genetic longevity-enhancing intervention targets and designing studies to test their effects.

    RESPONSIBILITIES

    The post-doctoral fellow will have the opportunity to develop and evaluate quantitative methods for interrogating genetically-mediated factors that impact human longevity and leverage them in the design and analysis of longevity-enhancing intervention studies. TGen provides a very collaborative environment that includes basic scientists, computational and quantitative scientists, biomedical technology developers and clinicians, including those at TGen's affiliated institution, the City of Hope Hospital in East Los Angeles, as well as its many other partner institutions.

    There is tremendous interest in the identification of factors that affect human longevity and potential interventions that enhance human longevity. Unfortunately, human longevity is a complex, multifactorial phenotype with a number of interacting genetic and non-genetic determinants. Characterizing the factors influencing longevity will be difficult since the effect of any one factor can be obscured by the effects of others. As a result, more sophisticated and integrated approaches are needed. This is true for both the identification and characterization of longevity-enhancing factors and testing longevity-enhancing interventions that target these factors. A research challenge will be to develop reliable techniques for mining data relevant to genetically-mediated factors (for example from genome-wide association studies focusing on longevity) to identify better longevity-enhancing intervention targets, as well as methods to test interventions that exploit those targets. In this context, the proposed activity and research will involve:
    • Modeling and the influence of genetic variants on human longevity using imputation and mediation tests
    • Developing strategies for identifying drugs and nutritional interventions that beneficially modulate longevity-associated factors
    • Designing studies to test interventions that target longevity-enhancing factors
    • Designing studies that measure factors that indicate changes consistent with a health benefit
    • Helping oversee the conduct of studies to identify and test factors that enhance longevity
    • Present findings on longevity enhancement at major conferences and in peer-reviewed publications
    TGen has access to resources (such as some of the largest and fastest computing systems in the world, a large phase I clinical trial center, a CLIA lab, genomic and other omic assay-oriented labs) that can be leveraged in the proposed research. In addition, the development of the proposed strategies and methods will likely have a broad, international impact, given the amount of attention human longeveity research is receiving, so the research to be pursued will be highly visible and competitive, and as a result could propel the career of an independently-minded researcher looking to make an indelible impact on a biomedical science and humanity in general.

    REQUIREMENTS

    • Ph.D. (completed or near completion) in Bioinformatics, Systems Biology, Computational or Quantitative Biology, Biostatistics, Statistics, Applied Mathematics, or a related field.
    • Computer programming, R and other statistical analysis packages, and scripting languages skills
    • Experience in developing linear and non-linear statistical models
    • An understanding of genetics and genomics
    • Experience with large biological data sets
    • Excellent written and verbal communication skills
    • Willingness to work in collaborative settings
    • No publication record is required, although a publication track record is preferred.

    ABOUT US

    About TGen:
    Translational Genomics Research Institute (TGen) is a Phoenix, Arizona-based non-profit organization dedicated to conducting groundbreaking research with life changing results. TGen is focused on helping patients with neurological disorders, cancer, and diabetes, through cutting edge translational research (the process of rapidly moving research towards patient benefit). TGen physicians and scientists work to unravel the genetic components of both common and rare complex diseases in adults and children. Working with collaborators in the scientific and medical communities literally worldwide, TGen makes a substantial contribution to help our patients through efficiency and effectiveness of the translational process. TGen is allied with City of Hope, a world-renowned independent research and cancer and diabetes treatment center. This precision medicine alliance enables both institutes to complement each other in research and patient care, with City of Hope providing a significant clinical setting to advance scientific discoveries made by TGen. For more information, visit: www.tgen.org.

    HOW TO APPLY

    If you are interested in seeing the most up to date job listings or to apply for this position, please go to www.tgen.org/careers-tgen/ and submit your resume. Please take a moment to read about our employee benefits and learn more about TGen. If you have any questions about the company or how to apply for a position, please contact hr[at]tgen.org.

    Only resumes submitted through the TGen career website will be considered.

    POLICY

    We value and support diversity in our workforce.
    EEO/AA

    BACKGROUND

    Dr. Nicholas Schork, Director of Quantitative Medicine at TGen, seeks a creative, independent, and highly motivated researcher interested in computational and general quantitative aspects of health and clinical learning systems (i.e., systems that can be used to make predictions about intervention strategies for individual patients based on large clinical and outcome data sets). Clinical learning systems have the potential to radically transform the way health care is delivered and monitored and have their root in large-scale electronic medical record systems, artificial intelligence and machine learning techniques and clinical decision support strategies.

    RESPONSIBILITIES

    The post-doctoral fellow will have the opportunity to develop and evaluate health learning systems in a collaborative environment that includes basic scientists, computational and quantitative scientists, informaticians and clinicians, including those at TGen's affiliated institution, the City of Hope Hospital in East Los Angeles, as well as its many other partner institutions.

    Learning systems in health care contexts take advantage of large amounts of data on patients (e.g., from Electronic Medical Records (EMRs)) to build predictive models that can be applied to future patients to determine sensible, if not optimal, courses of action based on their characteristics (e.g., genetic profile, past medical history, etc.). Such systems can be updated in real time given the continual patient accrual in clinical care settings. The design and implementation of such systems is receiving greater and greater attention, but present a number of challenges. For example, how can one harmonize relevant data in real time? What statistical analysis techniques should be used to develop the predictive models (e.g., deep learning)? How can such systems be coordinated across clinical entities to leverage even more data? The research questions and activities to be pursued in these contexts include:
    • Modeling and simulating the behavior of real-time clinical learning systems
    • Developing reliable, beyond state-of-the-field data-based analytic methods for guiding clinical decisions
    • Comparing different machine learning and statistical predictive analytic methods for their flexibility, robustness and reliability on simulated and real data
    • Developing strategies to integrate a wide variety of data types (e.g., genomics, imaging, wireless devices, etc.)
    • Beta-testing the implementation of novel systems with potential industry and academic partners
    • Helping oversee the implementation of systems and consulting on any issues that arise
    • Present findings on learning systems at major conferences and in peer-reviewed publications
    TGen has access to some of the largest and fastest computing systems in the world that can be leveraged in the proposed research. In addition, the development of health learning systems will likely have a broad, international impact, so the research to be pursued will be highly visible and competitive and as a result could propel the career of an independently-minded researcher looking to impact others on a large scale.

    REQUIREMENTS

    • Ph.D. (completed or near completion) in Computer Science, Operations Research, Informatics, Statistics/Biostatistics, Mathematics or a related field
    • Exceptional computer programming skills
    • Familiarity with state-of-the-field machine learning and statistical analysis techniques
    • Experience with large, heterogeneous data sets
    • Excellent written and verbal communication skills
    • Willingness to work in clinical decision-making settings
    • Willingness to travel when necessary to collaborating sites
    • No publication record is required, but a publication track record is preferred.

    ABOUT US

    About TGen:
    Translational Genomics Research Institute (TGen) is a Phoenix, Arizona-based non-profit organization dedicated to conducting groundbreaking research with life changing results. TGen is focused on helping patients with neurological disorders, cancer, and diabetes, through cutting edge translational research (the process of rapidly moving research towards patient benefit). TGen physicians and scientists work to unravel the genetic components of both common and rare complex diseases in adults and children. Working with collaborators in the scientific and medical communities literally worldwide, TGen makes a substantial contribution to help our patients through efficiency and effectiveness of the translational process. TGen is allied with City of Hope, a world-renowned independent research and cancer and diabetes treatment center. This precision medicine alliance enables both institutes to complement each other in research and patient care, with City of Hope providing a significant clinical setting to advance scientific discoveries made by TGen. For more information, visit: www.tgen.org.

    HOW TO APPLY

    If you are interested in seeing the most up to date job listings or to apply for this position, please go to www.tgen.org/careers-tgen/ and submit your resume. Please take a moment to read about our employee benefits and learn more about TGen. If you have any questions about the company or how to apply for a position, please contact hr[at]tgen.org.

    Only resumes submitted through the TGen career website will be considered.

    POLICY

    We value and support diversity in our workforce.
    EEO/AA

    BACKGROUND

    Dr. Nicholas Schork, Director of Quantitative Medicine at TGen, seeks a creative, independent, and highly motivated researcher interested in developing and applying novel and comprehensive annotation methods for genes and genetic variants in a wide variety of contexts, in particular disease diagnosis, therapeutic choice and cross-species (orthology) disease model analyses. The methods to be developed will consider modeling the influence of genetic variants on gene function and the functional effects of genes that can be reconciled across species.

    RESPONSIBILITIES

    The post-doctoral fellow will have the opportunity to develop and evaluate computationally-based gene and genetic variant functional models in a collaborative environment that includes basic scientists, computational and quantitative scientists, biomedical technology developers, evolutionary biologists and clinicians, including those at TGen's affiliated institution, the City of Hope Hospital in East Los Angeles, as well as its many other partner institutions.

    Variant functional annotation and orthology assessment methods are being developed rapidly. In addition, databases harboring information about the likely influence of genes and genetic variants in pathway and network contexts exist and continually being refined (e.g., the GTEX databases). Finally, large-scale functional studies using emerging model systems and in vitro assays such as CRISPR screens are being pursued to generate information that needs to be mined and reconciled. The challenge will be to integrate all of this into more comprehensive models of gene function and leverage them to make claims about the health status of individuals, the likely benefits of specific gene-targeting therapeutics, and the utility of specific model systems to understand disease pathogenesis. In this context, the proposed activity and research will involve:
    • Modeling and the influence of genetic variants on gene expression, protein structure and function, splicing, and other molecular physiologic processes
    • Considering the combined influence of multiple genetic variants on gene function
    • Developing models that consider compensatory and feedback mechanisms in networks and biological processes
    • Developing methods that leverage sequence orthology and homology across different species to assess function
    • Contributing to the development of software and webtools that implement the models to be developed
    • Participating in the implementation and evaluation of the application of the models to be developed
    • Present the models at major conferences and in peer-reviewed publications
    TGen has access to some of the largest and fastest computing systems in the world that can be leveraged in the proposed research. In addition, the development of the proposed models will likely have a broad, international impact, given the amount of attention genetics and genomics research is receiving, so the research to be pursued will be highly visible and competitive, and as a result could propel the career of an independently-minded researcher looking to make an indelible impact on a biomedical science.

    REQUIREMENTS

    • Ph.D. (completed or near completion) in Bioinformatics, Systems Biology, Computational or Quantitative Biology, Biostatistics, Comparative Biology, or a related field.
    • Computer programming, R, scripting languages, and biological database query skills
    • Familiarity with genomics and comparative biology
    • Experience with large biological data sets
    • Excellent written and verbal communication skills
    • Willingness to work in collaborative settings
    • No publication record is required, but a publication track record is preferred

    ABOUT US

    About TGen:
    Translational Genomics Research Institute (TGen) is a Phoenix, Arizona-based non-profit organization dedicated to conducting groundbreaking research with life changing results. TGen is focused on helping patients with neurological disorders, cancer, and diabetes, through cutting edge translational research (the process of rapidly moving research towards patient benefit). TGen physicians and scientists work to unravel the genetic components of both common and rare complex diseases in adults and children. Working with collaborators in the scientific and medical communities literally worldwide, TGen makes a substantial contribution to help our patients through efficiency and effectiveness of the translational process. TGen is allied with City of Hope, a world-renowned independent research and cancer and diabetes treatment center. This precision medicine alliance enables both institutes to complement each other in research and patient care, with City of Hope providing a significant clinical setting to advance scientific discoveries made by TGen. For more information, visit: www.tgen.org.

    HOW TO APPLY

    If you are interested in seeing the most up to date job listings or to apply for this position, please go to www.tgen.org/careers-tgen/ and submit your resume. Please take a moment to read about our employee benefits and learn more about TGen. If you have any questions about the company or how to apply for a position, please contact hr[at]tgen.org.

    Only resumes submitted through the TGen career website will be considered.

    POLICY

    We value and support diversity in our workforce.
    EEO/AA
    Opportunity: Data Scientist @ BERG -- Framingham, MA (US)
    Submitted by Slava Akmaev; posted on Friday, January 19, 2018

    BACKGROUND

    The Research Analytics team is seeking a highly motivated and experienced individual for a rapidly growing multi-disciplinary team. The candidate will be instrumental in the analysis and interpretation of high-throughput molecular data. The ideal candidate should have solid Data Sciences background and be strongly goal oriented with a focus on real world impact.

    RESPONSIBILITIES

    Provide statistical and bioinformatics analyses of high-throughput molecular data, Interact with internal and external collaborators to understand, design and develop the requested solutions. Develop and execute data analysis protocols to support company's discovery pipeline.Present scientific results internally and externally. Prepare and submit scientific manuscripts for review and publication.

    REQUIREMENTS

    Requires a PhD in Bioinformatics, Statistics, Applied Math, Computer Sciences or related field with a 0-3 years of experience; or a MS with 5-7 years of industry experience. Proficiency in R is required. Experience in Bioconductor is preferred. Experience in Linux and Big Data technologies. Experience in Scala, C, Python and MySQL is a plus. Experience in working with multiomic data is a plus. Proven ability to find creative and practical solutions to complex problems. Proven experience in applying Data Science methodologies to extract, process and transform data from multiple sources. Proven ability to deliver outputs in a comprehensive format that highlights major trends, avoid miss-interpretations and value the conclusions. Proven ability to demonstrate attention to detail and record keeping. Quick learner, extremely flexible and adaptable to the needs of internal collaborators in a dynamic environment. Ability to efficiently work in multiple projects. Must be able to work in team-oriented environment.

    TERMS

    This is a full-time, regular position with a competitive benefits package, generous time off offering and new hire stock option eligibility.

    LOCALE

    Framingham, MA

    COMPENSATION

    Up to $110k commensurate with applicable experience.

    HOW TO APPLY

    Visit berghealth.com/careers/ to apply online.

    DEADLINE

    None.

    POLICY

    Berg, LLC is an Equal Opportunity Employer.
    Opportunity: Project Manager @ BERG -- Framingham, MA (US)
    Submitted by Slava Akmaev; posted on Friday, January 19, 2018

    BACKGROUND

    The Analytics team is seeking a highly motivated, experienced and proactive individual to work closely with the team managers. Reporting into the Project Management Function, the incumbent will be responsible for overseeing execution on internal and external projects. The incumbent should have experience in Bioinformatics or other Biology driven quantitative discipline. The incumbent should also be a quick learner, extremely flexible and able to adapt to needs of the company.

    RESPONSIBILITIES

    Provide daily project execution for the Berg Analytics team. Work closely with the research teams and help trouble shoot minor issues to keep workflow constantly moving while maintaining time and quality.

    REQUIREMENTS

    Requires an M.S. in Life Sciences or a quantitative discipline with 2-5 years' industry experience as a Project Manager in Pharma or Healthcare. Must have demonstrated ability to "get things done" with a proven ability to find creative, practical solutions to complex workflow problems. Excellent communication and interpersonal skills combined with superior and proven track record of technical and organizational skills. Must be able to work in team-oriented environment and demonstrate attention to detail and record keeping.

    TERMS

    This is a full-time, regular position with a competitive benefits package, generous time off offering and new hire stock option eligibility.

    LOCALE

    Framingham, MA

    COMPENSATION

    Up to $110k commensurate with applicable experience.

    HOW TO APPLY

    Visit berghealth.com/careers/ to apply online.

    DEADLINE

    None

    POLICY

    Berg, LLC is an Equal Opportunity Employer.

    BACKGROUND

    Description: The mission of the Center for Molecular Oncology (CMO) is to promote precision oncology through genomic analysis to guide the diagnosis and treatment of cancer patients. The CMO brings together clinicians and scientists throughout MSKCC to conduct large-scale translational research involving molecular characterization of patient tumor specimens in order to identify correlations between genomic features and clinical outcomes.

    RESPONSIBILITIES

    The Platform Informatics group within the CMO is seeking a software engineer to build tools and improve existing infrastructure for patient sample tracking in next-generation sequencing analysis work flows. This technology is at the core of this center's mission to advance our knowledge of cancer using clinical data, biological research, computer science and statistics. Work will be performed in a small group atmosphere (approximately 10 members from diverse disciplines) with several active collaborators, and in concert with other LIMS Engineers, Project Managers, and genomic sequencing core scientists.

    REQUIREMENTS

    You Are:
    • A software engineer committed to applying programming skills for research discovery and clinical benefit
    • Interested in the analysis of large genomic datasets and the development of new clinical technologies
    • An expert with UNIX/Linux command line
    • A person who enjoys working in a team, is self-motivated, can manage multiple tasks simultaneously, and can solve problems independently
    You Have:
    • Masters or equivalent in computer science, bioinformatics, computational biology or other applied science with at least 2 years of software development experience
    • Familiarity with genomic data and metadata
    • Advanced experience in object-orientated programming (preferably JAVA), additional experience with python and angularjs a plus
    • Thorough experience with relational databases
    • Experience with Laboratory Information Management Systems; specifically, Sapio Sciences Exemplar LIMS
    • Familiarity with software testing methodologies and concepts
    • Ability to apply troubleshooting techniques to resolve complex, cross functional issues
    • Demonstrated ability to work independently and meet deadlines as a member of a team
    • Strong organizational and troubleshooting abilities, attention to detail and accuracy
    • Excellent written and verbal communication skills to interact with both biologists and IT professionals

    TERMS

    Duration: Full Time

    HOW TO APPLY

    Via website bit.ly/2DqTUW1 and email bic-recruit[at]cbio[dot]mskcc[dot]org. Please include #LIMS_ENG_2018 in the subject line.

    BACKGROUND

    Description: The mission of the Center for Molecular Oncology (CMO) is to promote precision oncology through genomic analysis to guide the diagnosis and treatment of cancer patients. The CMO brings together clinicians and scientists throughout MSKCC to conduct large-scale translational research involving molecular characterization of patient tumor specimens in order to identify correlations between genomic features and clinical outcomes.

    RESPONSIBILITIES

    The Platform Informatics group within the CMO is seeking a Bioinformatics Engineer Lead to be a software team manager responsible for engaging in and directing the design and implementation of variant calling pipelines from large-scale genomic data sets. This Bioinformatics Engineer Lead will work in a dynamic and exciting academic environment at the nexus of cancer biology, computer science, statistics and clinical research. Work will be performed in a small group atmosphere (approximately 10 members from diverse disciplines) with several active collaborators, and in concert with other Bioinformatics and Software Engineers. The Platform Informatics software team is responsible for developing data analysis pipeline frameworks and analytic platforms on both local high performance computing clusters and cloud-based resources to facilitate research activities and precision health initiatives. This position will directly contribute toward the evolution of our infrastructure design that leverages the Common Workflow Language (CWL) specification and a container-based systems approach that enable compute portability and reproducibility.

    REQUIREMENTS

    You Are:
    • A software manager committed to applying programming skills for research discovery and clinical benefit
    • Interested in the analysis of large genomic datasets and the development of new clinical technologies
    • Interested in enabling open, reproducible research
    • Familiar with genomic data and metadata
    • Familiar with source control systems, preferably Git
    • Familiar with software testing methodologies and concepts
    • An expert with the UNIX/Linux environment and clustered computing
    • Someone who thrives in a fast-paced, dynamic environment with changing priorities
    • A person who enjoys working in a team, is self-motivated, can manage multiple tasks simultaneously, and can solve problems independently
    • Self-directed individual with the ability to both contribute and lead a team of technical peers
    You Need:
    • Masters, PhD or equivalent in computer science, bioinformatics, computational biology or other applied science with software development experience
    • Demonstrated ability to manage software development in a small team environment
    • Hands-on expertise running bioinformatics pipelines on genomics data
    • Advanced knowledge of scripting and programming languages such as Java, C/C++, Python, Ruby, Perl and bash/csh/ksh
    • Significant experience with software container technologies such as Docker and/or Singularity
    • Experience with porting programs to Docker/Singularity containers; experience with deploying and using Docker/Singularity containers
    • Experience using of CWL (Common Workflow Language)
    • Experience running bioinformatics analyses using pipelines on the cloud (AWS and/or Google)
    • Ability to apply troubleshooting techniques to resolve complex, cross functional issues
    • Strong organizational skills, attention to detail and accuracy
    • Excellent written and verbal communication skills to interact with both biologists and IT professionals

    TERMS

    Duration: Full Time

    HOW TO APPLY

    Via website bit.ly/2riO7wc and email bic-recruit[at]cbio[dot]mskcc[dot]org. Please include #BIO_ENG_LEAD_2018 in the subject line.

    BACKGROUND

    Description: The mission of the Center for Molecular Oncology (CMO) is to promote precision oncology through genomic analysis to guide the diagnosis and treatment of cancer patients. The CMO brings together clinicians and scientists throughout MSKCC to conduct large-scale translational research involving molecular characterization of patient tumor specimens in order to identify correlations between genomic features and clinical outcomes.

    RESPONSIBILITIES

    Job Details:
    As a Computational Biologist / Bioinformatics Analyst you will:
    • Provide bioinformatics support in the development of next-generation sequencing applications to characterize the full spectrum of 
clinically significant genetic mutations in patient tumors
    • Design, implement and operate computational pipelines for the analysis of next-generation sequencing data
    • Evaluate and test third party software packages; evaluate performance of novel technology platforms and assays
    • Work with experimental and computational biologists, clinical and translational research collaborators, and scientists in the MSKCC Center for Molecular Oncology
    • Present results and progress updates at group meetings and make presentations to scientific and clinical collaborators
    • Attend seminars, lectures, and training courses to learn new computational biology skills to remain up to date with the cancer 
genomics field and learn new programming languages or techniques as necessary
    • Track specimen information, experimental and analysis parameters, performance metrics, and genomic results in databases

    REQUIREMENTS

    You are: 

    • An excellent problem-solver with the ability to analyze situations, draw conclusions, make recommendations and convey this information in a timely and proficient manner

    • A person who enjoys working in a team, is self-motivated, can manage multiple tasks simultaneously, and can solve problems independently
    • Interested in the analysis of large genomic datasets and the development of new clinical technologies
    • A detail-oriented, effective communicator with an ability to build strong relationships
    You have:
    Minimum Qualifications:
    • PhD with 0-2 years or Master's degree with 2-4 years of applied next-generation sequencing bioinformatics experience
    • Strong cross-disciplinary analytic skills, with broad experience in next-generation sequencing data analysis, bioinformatics methods, and database management
    • Experience with the UNIX/Linux environment and cluster computing
    • Advanced skills in Python (preferred), Ruby or Perl
    • Strong organizational and troubleshooting abilities, attention to detail and accuracy, and excellent oral and written English communication skills

    PREFERENCES

    Additional Desired Qualifications:
    • Computational biology / bioinformatics research experience in cancer genomics
    • Cloud computing experience
    • Experience with R

    TERMS

    Duration: Full Time

    HOW TO APPLY

    Via website bit.ly/2lkwLac and email bic-recruit[at]cbio[dot]mskcc[dot]org. Please include #CB2018 in the subject line.

    BACKGROUND

    Applications are invited for an experienced and highly motivated individual to lead the training of biomedical scientists in data science and computational biology skills. The successful candidate will play a key role in a new strategic programme in Computational Biology and Biomedical Data Science Training within the Centre for Computational Biology in the MRC Weatherall Institute for Molecular Medicine. The programme's mission is to provide substantial expertise and to add value to ongoing research across the University of Oxford by training and mentoring biomedical scientists in data science and computational biology skills, methods and working practices.

    RESPONSIBILITIES

    The Computational Biology Trainer will be involved in the day-to-day management of the programme, including planning and delivering bioinformatics training, supervising fellows in computational biology research projects, and leading collaborative research projects in computational genomics.

    REQUIREMENTS

    You will hold a PhD in a quantitative discipline e.g. computational biology, bioinformatics, physics, statistics or related discipline. Previous experience in organising and delivering data science/computational biology training is essential. You will have experience of working in a Linux operating system and proficient in a least one programming language (e.g. Python, R). Excellent interpersonal and communication skills, with the ability to convey concepts to other scientists in different fields of research are essential. Experience in computational genomics is highly desirable.

    TERMS

    The position is available full-time and fixed-term until 31 March 2021, funded by the Oxford Biomedical Research Centre. Applications from those wishing to work part-time as a 50% job share are welcome (please state this clearly in your application).

    LOCALE

    Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, MRC WIMM Centre for Computational Biology, John Radcliffe Hospital, Headington, Oxford

    COMPENSATION

    Grade 8: £39,922 - £47,722 p.a.

    HOW TO APPLY

    Applications for this vacancy are to be made online. You will be required to upload a CV and supporting statement as part of your online application. www.recruit.ox.ac.uk/pls/[...]32940

    DEADLINE

    The closing date for this position is 12.00 noon on Monday 19 February 2018. Interviews will be held in early March 2018.

    BACKGROUND

    The Ressom Lab (omics.georgetown.edu) at Georgetown Lombardi Comprehensive Cancer Center has an immediate opening for a post-doctoral research associate in bioinformatics to work in a multi-disciplinary environment on cancer biomarker discovery and systems biology research.

    RESPONSIBILITIES

    The candidate will be responsible for analysis of omic data acquired by high-throughput technologies such as mass-spectrometry and next generation sequencing. This includes: (1) pre-processing of mass-spectrometric and next generation sequencing data; (2) identification of differentially altered molecules by statistical and network-based methods; and (3) integration of multi-omic data by network-based and machine learning methods to identify cancer biomarkers and to advance systems biology research.

    REQUIREMENTS

    The position requires a Ph.D. degree in bioinformatics, computer science, engineering, biostatistics, or related field with relevant experience in computational biology. In addition, applicants should have demonstrated research experience in omic data analysis and machine learning methods such as deep learning.

    PREFERENCES

    Programming skills in R, MATLAB, or Python are highly desirable.

    COMPENSATION

    $48,000 - $55,000 per year

    HOW TO APPLY

    Applicants are requested to email their CV and names of three references to Prof. Ressom at hwr[at]georgetown.edu

    BACKGROUND

    Cancer is a major cause of death and suffering. It constitutes a group of diseases characterized by abnormal cell growth, stage-wise progression, heterogeneity, and potential to develop resistance to therapies. All these aspects are consequences of the evolutionary nature of cancer. Fortunately, genomics has recently begun to provide opportunities for unprecedentedly detailed insights into tumour evolution. New techniques are presently emerging for assaying the spatial distribution of tumour heterogeneity, and future yet unforeseen experimental breakthroughs are inevitable.

    CONTRA (itn-contra.org) is a H2020 Marie-Sklodowska-Curie Innovative Training Network aimed at providing a structured training programme to 15 Early Stage Researchers (ESRs) to study tumor evolution using computational techniques upon novel experimental data including, but not limited to, single-cell genomic data. See the list of projects at the end of this message.

    The training structure of CONTRA will include local and network-wide activities and secondments to other labs in the network. Most positions are for 3 years and some for 4 years, contracts starting approximately July 1, 2018, but all of them lead to a PhD degree.

    For individual descriptions of the 15 projects, please use the following link: itn-contra.org/esr-projects/.

    List of projects, including supervisor and host institution:
    ESR1: Comparing tumour phylogenies from single cell data versus bulk sequencing data. Florian Markowetz, University of Cambridge, Cambridge, UK.
    ESR2: The mechanisms of coding and non-coding oncogenic alterations. Nuria Lopez-Bigas, IRB, Barcelona, Spain.
    ESR3: Identification of drivers of relapse and metastasis. Nuria Lopez-Bigas, IRB, Barcelona, Spain.
    ESR4: Estimating tumour phylogenies from single-cell SNV and CNA data. Niko Beerenwinkel, ETH Zurich, Basel, Switzerland.
    ESR5: Evolutionary history of circulating tumour cells and distant metastases. Ewa Szczurek, University of Warsaw, Warsaw, Poland.
    ESR6: Identification and impact of clonal and subclonal driver alterations on cancer progression. Francesca Ciccarelli, KCL/Crick Institute, London, UK.
    ESR7: Inferring tumour evolution and migration. Niko Beerenwinkel, ETH Zurich, Basel, Switzerland.
    ESR8: Models and inference for Single-cell sequencing and tumour evolution. Jens Lagergren, KTH, Stockholm, Sweden.
    ESR9: Evolution of drug resistance on genetic and phenotypic levels. Ewa Szczurek, University of Warsaw, Warsaw, Poland.
    ESR10: Driver events, evolutionary dynamics and interplay with the external environment across cancer types. Francesca Ciccarelli, KCL/Crick Institute, London, UK.
    ESR11: Estimation of tumour growth rates from NGS data. David Posada, University of Vigo, Vigo, Spain.
    ESR12: Mutational patterns and models within tumours. David Posada, University of Vigo, Vigo, Spain.
    ESR13: Integrated image and genomics. Yinyin Yuan, ICR, London, UK.
    ESR14: Spatial genetics and transcriptomics of pancreatic and ovarian cancer. Florian Markowetz, University of Cambridge, Cambridge, UK.
    ESR15: Reconciling tumour trees and multiple tumour progression models. Jens Lagergren, KTH, Stockholm, Sweden.

    COMPENSATION

    H2020 EU funding imposes strict eligibility criteria. At the time of recruitment the researcher must not have resided or carried out his/her main activity (work, studies, etc...) in the country of the host institute for more than 12 months in the three years immediately prior to his/her recruitment. The researcher should also be in the first four years of their research careers at the time of recruitment by the host organisation and have not been awarded a doctoral degree. The successful candidate will receive a very generous financial package. The exact conditions varies across the universities, but the gross amounts of EU funding for an ESR is in the range 3710€-4210€. The net salary will result from deducting all compulsory (employer/employee) social security contributions as well as direct taxes from the gross amounts, according to the law applicable to the agreement concluded with the ESR. Some universities will also supplement the EU funding. For details see the EU Guide for applicants (goo.gl/d6LtsE).

    HOW TO APPLY

    Candidates may apply for the positions through the KTH application system (goo.gl/yTThgg). The application should include the following documents:
    1. Curriculum vitae with at most 3 pages
    2. Transcripts from University / University College
    3. Contact details for three references
    4. Brief description of why the applicant wishes to become a PhD student within this network
    5. Ranking of 3 ESR projects based on the applicant's preference

    Each project supervisor will revise the candidates' documentation and, on the basis of the completeness and adequacy of the requested material and eligibility, will score candidates based on: (1) academic profile; (2) personal motivation; (3) scientific skills and relevant experience; and (4) English proficiency. Shortlisted candidates will be invited to teleconference interviews with the relevant project supervisor(s).

    Candidates are invited to contact the supervisors for more details.

    DEADLINE

    Application deadline: 23:59 CET on 15 February 2018.

    POLICY

    Specific conditions may apply to individual positions depending on local regulations. Top-level graduates (master degree or equivalent) in bioinformatics, statistics, mathematics, computer science or evolutionary biology are encouraged to apply. No discrimination will be made on the basis of nationality, gender, race, religion or disability.

    BACKGROUND

    The Center for Systems Biology Dresden (CSBD) calls for applications for ELBE postdoctoral fellowships in the fields of

    Bioinformatics and Computational Biology

    The ELBE postdoctoral fellows program fosters cross-disciplinary projects and provides an ideal springboard to an independent research career.

    REQUIREMENTS

    What we seek:
    We seek outstanding young researchers with a doctoral degree in computer science, (applied) mathematics, or bioinformatics and a strong commitment to work in a multi-disciplinary environment on Biological Sequence Analysis, Bioimage Informatics, Computer Simulation of biological systems, Comparative and Evolutionary Genomics, High-Performance Computing, or Network Biology. ELBE postdoctoral fellows are expected to collaborate with more than one research group to bridge between disciplines.

    COMPENSATION

    What we provide:
    The CSBD provides 1-3 year fully funded positions in an international and cross-disciplinary research environment. ELBE postdoctoral fellows benefit from close collaborations with scientists at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), the Max Planck Institute for the Physics of Complex Systems (MPI-PKS), and the Technische Universität Dresden (TU Dresden). They have full access to state-of-the-art research facilities and infrastructure on the campus. ELBE postdoctoral fellows have the freedom to develop their own research questions.

    HOW TO APPLY

    For details about the application procedure, please visit our website: www.csbdresden.de/join[...]tdoc/. Selection of ELBE Fellows is highly competitive with two application cycles per year. Short-listed candidates are invited to on-site interviews with travel costs covered by the CSBD.

    DEADLINE

    Deadline for applications is March 4, 2018.

    POLICY

    The Max Planck Society is an equal opportunity employer: handicapped individuals are strongly encouraged to apply. The Center for Systems Biology, the MPI-CBG and the MPI-PKS aim to increase the number of women in scientific positions. Female candidates are therefore particularly welcome.

    BACKGROUND

    Are you experienced at setting up and maintaining data-warehouses interfacing with various public or restricted databases, and interested in research data and workflow management systems? Do you have programming skills to support your work in manipulating the data flow between databases, file systems, third party software and front-end systems? Do you have experience in handling sensitive data, and setting high IT safety standards? Do you have experience in development and use of bioinformatics tools in life science / health research environment?

 The Department of Bio and Health Informatics at the Technical University of Denmark (DTU Bioinformatics) is seeking a highly skilled Bioinformatics Database Architect and scientific computing programmer. The position is available immediately with possibilities to negotiate the start date for the right candidate.

 The department offers an eclectic highly international environment of diverse and dynamic scientific researchers, working with diverse sets of biological data with activities spanning Health, Personalized Medicine, Biotechnology, and Artificial Intelligence, and is one of the largest and permanent stakeholders of the national life science and biomedical super-computing center – Computerome. 

As Database Architect / Manager, you will be an important member of the administrative team. You will refer directly to the Head of Department, but cooperate closely with the department's researchers.

    RESPONSIBILITIES

    Primary areas of responsibility:
    Your main responsibility will be to maintain the clinical, biological, experimental, genomic and other multi-omic data-warehouse and secure that various public or restricted databases are updated regularly on legacy infrastructure. As senior Data Architect and Manager, you will interface with scientists to assist with data design and help with workflow management. You will have responsibilities to handle DTU Bioinformatics data warehouse including database design and data modelling, in addition to developing web user interfaces and custom web servers. You will furthermore be involved in close cooperation with research scientists, assisting with programming efforts, bioinformatics software tool development, data design and workflow management.

 The department works in close collaboration with DTU corporate IT, where you will be expected to contribute to data security and research data management in accordance with various IT and Public Health security standards.

 DTU Bioinformatics collaborates with hospitals, biotech (genotyping and next-generation sequencing) laboratories, animal/aqua/veterinary/food/microbial research institutes, universities and public organizations, where your expertise will be utilized in collaboratory projects (both internal and external), and good communication skills will be expected.

    REQUIREMENTS

    
The following skills are required with proven experience:
    • Unix/Linux use and administration
    • Database skills, preferably MySQL, in design, maintenance, query and performance
    • Web technologies; HTML, CSS, JS and CGI
    • Programming, preferably Perl or Python
    • R programming
    Highly desirable:
    • Life or health sciences education or experience
    • Experience with NGS, GWAS data
    Nice to have:
    • Human interface design
    • High Performance Computing
    • Parallel programming
    • Machine learning
    • Big Data integration and visualisation
    You have at least an M.Sc. in computer science, software engineering or in bioinformatics or a related discipline, preferably with 3-5 years of work experience.

Strong proficiency in English (written and oral), experience working in teams, multi-tasking across projects, as well as proven ability for independent execution and initiative are valued due to our international work environment and multiple stakeholders.

    COMPENSATION

    What we offer in return
:
    In recent years, DTU has been working concertedly to professionalize management. The DTU Leadership Role is based on four cornerstones: academic management, resource management, Performance-enhancing HR management and strategic management. Moreover, self-management and DTU's values constitute the central parameters for these four disciplines. To find out more about DTU's Leadership Role, see the website (www.bioinformatics.dtu.dk/english).

    Salary and terms of employment:
    
The appointment will be based on the collective agreement with the Confederation of Professional Associations (AC) or another relevant union. The allowance will be agreed with the relevant union.



    LOCALE

    Place of employment will be at DTU Lyngby Campus, DTU Bioinformatics.



    HOW TO APPLY

    Application and contact
Please submit your online application no later than Friday 16 February 2018.

    You can apply for the position online at www.career.dtu.dk.

    To apply, please open the link "Apply online," fill in the online application form, and attach all documents in English. 
Your application must include:
    • A motivational letter accompanying the application (cover letter)
    • CV
    • Grade transcripts and BSc/MSc diploma
    • Names and address of at least two referees
    If you would like additional information about the position, please contact Head of Department, Professor Haja Kadarmideen, at +45 4525 6161 or director[at]bioinformatics.dtu.dk

    ABOUT US

    DTU Bio and Health informatics (www.bioinformatics.dtu.dk/english) is operating at the highest level of research, teaching, innovation, and consultancy services within the areas biotechnological informatics, health informatics, quantitative genomics and systems biology. The department's activities in the fields of research, teaching, scientific advice, and innovation are centered on the following research areas: health, cancer, obesity/diabetes, immunology, infectious diseases, proteins, molecular biology, and molecular mechanisms, animal, plant & microbial genomics and biotechnology and big data infrastructure.

 DTU is a technical university providing internationally leading research, education, innovation and public service. Our staff of 5,700 advance science and technology to create innovative solutions that meet the demands of society; and our 10,000 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government, and public agencies.

    POLICY

    All interested candidates, irrespective of age, gender, race, disability, religion or ethnic background, are encouraged to apply.
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