AI Cell Physiology Modeling Postdoctoral Fellow

Berkeley Lab • Berkeley, CA

8d • Onsite

About The Position

Berkeley Lab’s (LBNL) Biological Systems and Engineering (BSE) Division has an opening for a Postdoctoral Fellow to join the Cellular Intelligence and BioAnalytics (CIBA) Group within the Advanced Bio Process Development Unit (ABPDU). In this role, you will develop AI-driven predictive metabolic models of cell physiology, metabolism, and functional behavior. You will receive hands-on training in mammalian cell culture, micro-respirometry, stable isotope tracing, and associated biochemical assays, providing a deep first-principles understanding of the biological systems being modeled. You will develop practical skills to maintain cell lines and conduct targeted experiments, and collaborate with experimentalists while developing and applying AI-driven models of cellular physiology. You will integrate and analyze datasets to advance predictive models of cellular metabolism and function. Training will start at UCLA for 3-4 months, followed by relocation to Berkeley Lab. Alternatively, immediate relocation to Berkeley Lab may be possible, followed by periodic visits to UCLA for training and/or collaboration. This position has an anticipated start date of October 1, 2026. Join our team to play a supporting role in addressing global challenges through science solutions.

Requirements

• A recent Ph.D. (within the last 1-2 years) in Computer Science, Chemical Engineering, Systems Biology, Bioengineering, Computational Biology, or a related discipline.
• Strong computational and machine learning skills, including research experience applying AI/ML models using complex experimental biology datasets.
• Demonstrated understanding of Cell Biology, through academic coursework, research experience, or wet-lab experience in Life-Sciences or related disciplines.
• Strong willingness and ability to participate in hands-on training onsite at UCLA to acquire wet-lab experimental skills, including cell culture, micro-respirometry, and biochemical assays.
• Strong analytical skills including the ability to identify problems, troubleshoot, and demonstrate good judgement in selecting methods and techniques for obtaining solutions.
• Excellent oral and written communication skills, including experience documenting research activities, analyzing results, and presenting findings for a variety of audiences.
• Demonstrated interpersonal skills, including experience collaborating with an interdisciplinary research team in a multi-disciplinary scientific or production environment.
• Less than 3 years of paid postdoctoral experience.

Responsibilities

• Develop research expertise by contributing to project goals, engaging constructively with collaborators, generating scientific insights, and progressively taking ownership of defined research activities under appropriate scientific mentorship.
• Develop, implement, train, and validate machine learning and deep learning models for AI-driven prediction of cell physiology, metabolism, and functional behavior, with input from the research team.
• Participate in hands-on research training at UCLA, including mammalian cell culture, micro-respirometry, stable isotope tracing, and associated biochemical assays, to develop a strong practical understanding of relevant cell biology experiments.
• Conduct targeted experiments and closely collaborate with experimentalists at UCLA to integrate experimental datasets generated at UCLA and LBNL into AI-driven predictive models.
• Prepare and publish rigorous research results in peer-reviewed scientific journals.
• Maintain well organized, thorough, and accurate laboratory documentation.
• Provide regular written and oral progress updates and facilitate technical discussions within the team.
• Prepare and present research findings at conferences and meetings with collaborators across industry, academia, and national laboratories.

Benefits

• Exceptional health benefits
• Generous paid time off, sick time off, and holidays
• A culture where you’ll belong

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree