Computational AI Postdoctoral Fellow

at  Lawrence Berkeley National Laboratory

Berkeley Lab’s (LBNL) Biological Systems and Engineering (BSE) Division has an opening for a Postdoctoral Fellow to join the Quantitative Modeling Group led by Héctor García Martín to develop machine learning algorithms, mechanistic models, data science pipelines, and automated workflows to design cells to produce renewable products and combat climate change. You will have the opportunity to help design cells to a specification, bring synthetic biology to its full potential, and enable self-driving labs.
In this exciting role, you will work as part of a collaborative team 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. 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, as part of the Agile BioFoundry and the Joint BioEnergy Institute.
This position has an anticipated start date of January 1, 2025.

DESIRED QUALIFICATIONS:

• Experience in metabolic flux analysis.
• Experience on experimental lab work.
• Knowledge of microbiology and microbial metabolism.
• Strong interest in microbiology and bacterial metabolism.

LEARN ABOUT US:

Berkeley Lab (LBNL) 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 16 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.
Working at Berkeley Lab has many rewards including a competitive compensation program, excellent health and welfare programs, a retirement program that is second to none, and outstanding development opportunities. To view information about the many rewards that are offered at Berkeley Lab- .
Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA) 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, “Equal Employment Opportunity is the Law” and the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4.

• Integrate and analyze data.
• Develop quantitative predictive models of cell metabolism.
• Integrate transcriptomic, proteomic, and metabolomic data into quantitative models.
• Use Monte Carlo approaches to more precisely measure and predict metabolic fluxes.
• Use machine-learning and data-mining approaches to improve bioproduct yields.
• Develop new machine-learning algorithms.
• Combine machine learning and mechanistic approaches.
• Develop and optimize code and algorithms for predictive models.
• Combine algorithms and automation to enable self-driving labs and automate the scientific process.
• Interact continuously with experimentalists and automation scientists to guide and propose new experiments and use available data to its full potential.
• Interact continuously with software engineers to provide code using best practices.
• Resolve problems that may affect the achievement of research objectives and deadlines.
• Prepare research results for publication and present at scientific and internal meetings.