Ph.D. in Systems Biology, Bioengineering, Computational Biology, or related field with 3+ years of AI application experience in biology.
Proficient in Python or other major programming languages.
Experience with deep learning techniques and methodologies.
Familiarity with lab automation and automated workflows.
Hands-on experience in experimental Synthetic Biology.
Strong mathematical skills for complex scientific problem-solving.
Excellent communication skills for diverse audiences.
Responsibilities
Apply AI and data science to enhance biomanufacturing processes.
Develop predictive models of cell metabolism.
Integrate multi-omics data into quantitative biological models.
Create AI agents for data analysis and research direction recommendations.
Design data management systems for biological data organization.
Collaborate with experimentalists to identify and propose new research opportunities.
Automate scientific workflows using robotic systems.
Prepare research findings for publication and presentations.
Assist in grant proposal preparation and submission.
Benefits
Full-time, career-track term appointment with potential for renewal.
Benefits eligible position with union representation.
Opportunity for professional development and team leadership.
Access to cutting-edge research facilities and interdisciplinary collaboration.
Engagement in impactful research that advances scientific discovery.
Full Job Description
Berkeley Lab's (LBNL) Biological Systems and Engineering (BSE) Division has an opening for a Computational Research Scientist to join the Quantitative Modeling Group led by Héctor García Martín!
In this exciting role, you will work towards making biology predictable by integrating artificial intelligence (AI), robotics, and synthetic biology. Under general supervision of the Principal Investigator (PI), you will leverage current and future funding to build and implement tools, technologies, and infrastructure that advance biomanufacturing through machine learning and automation. You will be expected to secure independent funding and develop a vigorous research program focused on the application of AI to advance scientific discovery and innovation.
This position has an anticipated start date of December 14, 2026.
What You Will Do:
Apply artificial intelligence and data science to guide and advance biomanufacturing.
Develop quantitative and predictive models of cell metabolism.
Integrate transcriptomic, proteomic, and metabolomic data into quantitative predictive models of biological systems.
Develop and orchestrate AI agents to analyze complex scientific data and recommend future research directions and experimental approaches.
Design and leverage data management systems to effectively organize, represent, and utilize biological data.
Collaborate closely with experimentalists to identify research opportunities, guide and propose new experiments, and use available data to its full potential.
Develop, integrate, and utilize robotic systems to automate scientific workflows and advance the development of self-driving labs.
Prepare research results for publication in scientific journals and presentation at scientific conferences, seminars, and internal meetings.
Assist with the preparation and submission of grant proposals and other funding applications.
May be responsible for their team's success and professional development.
What is Required:
A Ph.D. (or equivalent knowledge/training) in Systems Biology, Bioengineering, Computational Biology, Bioinformatics, Applied Mathematics, Physics, Computer Science, Chemical Engineering, Electrical Engineering or a closely related discipline and minimum of 3 years of relevant experience applying artificial intelligence to guide and inform biological experiments or an equivalent combination of education and experience.
Significant experience with Python or other major programming languages.
Experience with deep learning techniques and methodologies.
Experience with lab automation and automated experimental workflows.
Experience with experimental Synthetic Biology and hands-on bench work.
A strong mathematical background including the ability to apply quantitative approaches to complex scientific problems.
Strong analytical skills including experience identifying issues, troubleshooting complex problems, and recommending appropriate solutions.
Excellent written and verbal communication skills including the ability to effectively communicate scientific concepts and research findings to a variety of audiences.
Demonstrated interpersonal skills including the ability to conduct collaborative research in an interdisciplinary team environment.
Desired Qualifications:
A Ph.D. in Systems Biology, Bioengineering, Computational Biology, Bioinformatics, Applied Mathematics, Physics, Computer Science, Chemical Engineering, Electrical Engineering or a closely related discipline.
Demonstrated ability to effectively supervise staff, including assigning work, providing coaching and performance feedback, and supporting employee development.
Additional Information:
Application Date: Priority consideration will be given to candidates who apply with a curriculum vitae (CV) or resume and a cover letter describing their interest in this position by November 16, 2026. Applications will be accepted until the job posting is removed.
Appointment Type: This is a full time, exempt from overtime pay (monthly paid), 2 year (benefits eligible),career-track term appointment that may be renewed to a maximum of 5 years and that may be converted to career based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs.
Union Represented: This position is represented by a union for collective bargaining purposes.
Salary Information: This position has a budgeted range of $94,740 - $151,580 annually for job code S39.1. It is not typical for an individual to be offered a salary at or near the top of the range for a position. Salary will be commensurate with the final candidate's qualification and experience, including skills, knowledge, relevant education, certifications, and aligned with the internal peer group (if applicable, and union contract agreement).
Background Check: This position is 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 Modality: Work will be performed onsite at the Emeryville Station East (ESE) Operations Center located in Building 978 at 5885 Hollis Street Emeryville, CA 94608. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here).
Relocation: This position is not eligible for relocation assistance.
Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov
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