Computational Biologist Research Scientist; Quantitative Modeling Group
Listed on 2026-10-11
-
Research/Development
Data Scientist, Research Scientist
Berkeley Lab's (LBNL) Biological Systems and Engineering (BSE) Division has an opening for a Computational Biologist Research Scientist to join the Quantitative Modeling Group led by Hector Garcia Martin!
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 leverage tools 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 1, 2026.
We're here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with
17 Nobel Prizes!
We invest in our employees by offering a total rewards package you can count on:
- Exceptional health benefits.
- Generous paid time off, sick time off, and holidays.
- A culture where you'll belong - we are invested in our teams!
- Apply artificial intelligence and data-mining approaches to guide and advance biomanufacturing.
- Develop quantitatively 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 continuously with experimentalists to guide and propose new experimental work, 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. This may involve recruiting talent with the right skills for their projects, directing daily work, and managing performance through feedback and clear expectations. Supervisors have the authority to take necessary actions, including performance management, to maintain the research group’s integrity and productivity.
- 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.
- Experience with lab automation and automated experimental workflows.
- Experience with experimental 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…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).