Computational Postdoctoral Fellow (Quantitative Modeling Group)

LBL$95K — $107K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. in relevant fields (Physics, Applied Mathematics, etc.) within the last 1-2 years.
  • Programming experience in Python or equivalent languages.
  • Proficient in Linux, including shell scripting and system monitoring.
  • Strong mathematical foundation with coursework or experience.
  • Organizational skills for maintaining detailed records.
  • Excellent communication skills, particularly in presenting research findings.
  • Interpersonal skills for collaborative, interdisciplinary teamwork.

Responsibilities

  • Integrate and analyze complex biological datasets.
  • Develop predictive models of biological systems.
  • Incorporate multi-omics data into computational models.
  • Utilize Monte Carlo methods to estimate uncertainty.
  • Apply machine learning techniques to suggest bioengineering solutions.
  • Create and optimize algorithms for predictive modeling.
  • Collaborate with scientists to enhance experimental design.

Benefits

  • Opportunity for relocation assistance.
  • Work in a collaborative, interdisciplinary environment.
  • Participation in cutting-edge research supporting bioengineering.
  • Potential for position renewal based on performance and funding.
  • Engagement in projects with national significance, including environmental and security applications.
Full Job Description
Berkeley Lab's (LBNL) Biological Systems and Engineering (BSE) Division has an opening for a Computational Postdoctoral Fellow to join the Quantitative Modeling Group led by Héctor García Martín!

In this exciting role, you will leverage Artificial Intelligence, data science, mechanistic models, robotics, and synthetic biology to enable quantitative predictions of biological systems and support the development of self-driving laboratories. You will contribute to the design of cells and other biological systems to a specification, with the final goal of enabling the full potential of biomanufacturing to create enhanced-performance products, diminish supply chain disruptions, produce environmental benefits, address national security needs, and create new jobs and industries.

You will have the opportunity to work collaboratively to integrate microbial phenotypic data (e.g., fluxomics, transcriptomics, proteomics, metabolomics) into quantitative computational models capable of predicting and explaining the outcomes of bioengineering interventions. You will work closely with an interdisciplinary team of bench scientists, automation engineers, and software engineers in devising methods for high-throughput data collection and analysis for feedback into experimental design. This work will support initiatives within the Agile BioFoundry, the Joint BioEnergy Institute, and/or other programs.

This position has an anticipated start date of September 1, 2026.

What You Will Do:

  • Integrate and analyze complex biological datasets.
  • Develop quantitatively predictive models of biological systems.
  • Integrate multi-omics data into quantitative computational models.
  • Apply Monte Carlo sampling approaches to quantify uncertainty.
  • Utilize machine-learning and data-mining approaches to recommend bioengineering interventions.
  • Develop new machine-learning algorithms.
  • Integrate machine learning techniques with mechanistic modeling approaches.
  • Develop, optimize, and maintain code and algorithms supporting predictive models.
  • Combine computational algorithms with laboratory automation to enable self-driving laboratories and automate the scientific process.
  • Collaborate closely with experimental and automation scientists to guide experimental design and maximize the value of available data to its full potential.
  • Partner with software engineers to develop and maintain code following best practices.
  • Troubleshoot technical and research problems that may affect the achievement of research objectives and deadlines.
  • Prepare research results for publication and present results at scientific conferences, seminars, and internal meetings.
  • Contribute to the preparation and development of grant proposals and related supporting materials.


What is Required:
  • A recent Ph.D. (within the last 1-2 years) in Physics, Applied Mathematics, Computer Science, Electrical Engineering, Chemical Engineering, Mechanical Engineering, Systems Biology, Bioengineering, Computational Biology, Bioinformatics, or a closely related discipline.
  • Demonstrated experience programming in Python or other major programming languages.
  • Proven experience working in Linux environments, including file systems, shell scripting, and hardware/software monitoring.
  • Strong mathematical background as evidenced by relevant coursework and/or work experience.
  • Strong organizational skills including experience maintaining detailed and accurate records of results and analyzed data.
  • Excellent verbal and presentation skills including experience preparing research reports, manuscripts, and scientific publications for group meetings, conferences, and scientific journals.
  • Demonstrated interpersonal communication skills including experience conducting independent, data-driven research and collaborating with an interdisciplinary research team.


Desired Skills/Knowledge:
  • Experience conducting experimental laboratory work.
  • Experience with metabolic flux analysis.
  • Knowledge of microbiology and microbial metabolism.
  • Strong interest in biology and metabolism.


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 July 31, 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), Postdoctoral Fellow appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. This position is represented by a union for collective bargaining purposes.
  • Salary Range: The salary range for this position is $7,987 - $8,921 monthly / $95,844 - $107,052 annually and is expected to start at $7,987 monthly / $95,844 annually or above. Postdoctoral positions are paid on a step schedule per union contract and salaries are predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral and/or related research experience.
  • 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: This position will be performed onsite at the Emeryville Station East (ESE) Operations Center located in Building 978 at 5885 Hollis Street Emeryville, CA 94608. Work schedules are dependent on business needs. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here).
  • Relocation Assistance: This position is eligible for relocation assistance.
  • Export Control Access: This position will involve access to hardware, commodities, and technical information subject to export control regulations including, but not limited to, the Export Administration Regulations ("EAR") and/or International Traffic in Arms Regulations ("ITAR"). Accordingly, any hiring decision may depend in part on Berkeley Lab's ability to obtain or rely on federal government authorizations as required, if you are not a U.S. citizen, lawful permanent resident of the U.S. ("green card holder"), asylee, refugee, or other qualifying protected individual as defined by 8 U.S.C. 1324b(a)(3).


Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov

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