Computational Biologist Project Scientist (Quantitative Metabolic Modeling Group) - 94678 Organization: BE-Biological Systems & Eng
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.
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).
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.
Notes: • 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. • Work will be performed onsite at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
How To Apply Apply directly online at http://50.73.55.13/counter.php?id=219269 and follow the on-line instructions to complete the application process.
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