Bioinformatics.org
[University of Birmingham]
[Georgetown University]
Not logged in
  • Log in
  • Bioinformatics.org
    Membership (43144+) Group hosting [?] Wiki
    Franklin Award
    Sponsorships

    Careers
    About bioinformatics
    Bioinformatics jobs

    Research
    All information groups
    Online databases Online analysis tools Online education tools More tools

    Development
    All software groups
    FTP repository
    SVN & CVS repositories [?]
    Mailing lists

    Forums
    News & Commentary
  • Submit
  • Archives
  • Subscribe

  • Jobs Forum
    (Career Center)
  • Submit
  • Archives
  • Subscribe
  • Career Center - Message forums

    Opportunity: Computational Biologist Project Scientist (Quantitative Metabolic Modeling Group) (#94678) @ Lawrence Berkeley National Laboratory -- Berkeley, CA (US)
    Submitted by Bill Cannan; posted on Saturday, January 22, 2022

    RESPONSIBILITIES

    Berkeley Lab's Biological Systems & Engineering Division (BSE) is looking for a Computational Biologist Project Scientist to join their Quantitative Metabolic Modeling Group!

    In this role, you will use Artificial Intelligence to design living cells for the production of renewable energy and bioproducts, and combat climate change. You will use Artificial Intelligence and Machine learning to make synthetic biology predictable, and enable a circular carbon economy.

    As part of the Quantitative Metabolic Modeling Group (https://qmm.lbl.gov), led by Héctor García Martín (http://hectorgarciamartin.com), you will work collaboratively to integrate microbial phenotypic data (e.g. fluxomics, transcriptomics, proteomics, metabolomics) into quantitative computational models able to predict and explain the outcomes of bioengineering interventions. As part of the Agile BioFoundry (https://agilebiofoundry.org/home/about/) at the Joint BioEnergy Institute (https://www.jbei.org), you will work closely with an interdisciplinary team of bench scientists, automation engineers, and software developers in devising methods for high-throughput data collection and analysis for feedback into experimental design.

    What You Will Do:
    • Develop quantitative predictive models of cell metabolism.
    • Integrate transcriptomic, proteomic, and metabolomic data into quantitative models.
    • Use machine-learning approaches to predict bioengineering outcomes.
    • Develop new machine-learning algorithms.
    • Develop and validate kinetic models for microbial metabolism.
    • Develop and optimize code and algorithms for predictive models.
    • Partner with bench scientists to guide and propose new experiments and use available data to its full potential.
    • Prepare research results for publication and for presentations at scientific and internal meetings.
    • Develop automated experiments in collaboration with automation engineers to gather data for predictive models.
    • Provide oversight and direction to a team of Students, Postdoctoral Fellows, and Research Associates.
    • Participate in group meetings, steering committee meetings, project retreats and seminars.
    • Assist in preparation of grant proposals.

    REQUIREMENTS

    What is Required:
    • A minimum of 3 years of relevant experience in Machine Learning beyond the highest customary degree in Systems Biology, Bioengineering, Computational Biology, Bioinformatics, Applied Mathematics, Theoretical Physics, Computer Science, Electrical Engineering, or a closely related discipline.
    • Significant experience in Python or other major programming languages.
    • Strong analytical skills and mathematical background.
    • Strong oral and written communication skills including the ability to accurately document results and present information.
    • Demonstrated interpersonal skills including the ability to perform collaborative research in an interdisciplinary team environment.
    What We Prefer:
    • PhD in Systems Biology, Bioengineering, Computational Biology, Bioinformatics, Applied Mathematics, Theoretical Physics, Computer Science, Electrical Engineering, or a closely related discipline.
    • Experience with Deep Learning techniques, Lab Automation (e.g. liquid handlers), Metabolic Flux Analysis, Experimental Metabolic Engineering bench work (e.g. construct design, gene knockout, cloning and expression).

    TERMS & COMPENSATION

    • This is a full time, exempt from overtime pay (monthly paid), 2 year, Term appointment with the possibility of renewal up to a maximum of 5 years total based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs.
    • Salary is commensurate with experience.
    • This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

    LOCATION

    Work will be performed onsite at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

    HOW TO APPLY

    For full consideration, please apply by February 9, 2022 with the following application materials:
    • Cover Letter – Describe your interest in this position and the relevance of your background.
    • Curriculum Vitae (CV) or Resume.
    Apply directly online at http://50.73.55.13/counter.php?id=219270 and follow the on-line instructions to complete the application process.

    ABOUT US

    Berkeley Lab (LBNL, http://www.lbl.gov) addresses the world's most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab's scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy's Office of Science.

    The Biological Systems & Engineering Division's vision is to lead efforts that combine the power of biology with the tools of engineering to develop sustainable energy and manufacturing solutions to improve human health.

    Berkeley Lab's Postdoc Program is committed to providing Postdoctoral Researchers and Visiting scholars with a positive and impactful experience to jump-start their career through premium research and career development, networking opportunities, mentoring programs, and a strong community. For more information, please visit our Berkeley Lab Postdoc Resources site (http://postdocresources.lbl.gov) and our Berkeley Lab Postdoc Association site (http://postdoc.lbl.gov).

    POLICY

    Based on University of California Policy – SARS-CoV-2 (COVID-19) Vaccination Program and U.S Federal Government requirements, Berkeley Lab requires that all members of our community obtain the COVID-19 vaccine as soon as they are eligible. As a condition of employment at Berkeley Lab, all Covered Individuals must Participate in the COVID-19 Vaccination Program by providing proof of Full Vaccination or submitting a request for Exception or Deferral. Visit covid.lbl.gov for more information.

    Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA, https://diversity.lbl.gov/ideaberkeleylab/) and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab's mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

    Equal Opportunity and IDEA Information Links:
    Know your rights, click here (http://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm) for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision (https://www.dol.gov/ofccp/PayTransparencyNondiscrimination.html) under 41 CFR 60-1.4.

    Expanded view | Monitor forum | Save place

    Start a new thread:
    You have to be logged in to post a reply.

     

    Copyright © 2022 Scilico, LLC · Privacy Policy