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Computational Chemistry and Data Analytics - Academic Graduate Appointee

Remote / Online - Candidates ideally in
Livermore, Alameda County, California, 94551, USA
Listing for: Lawrence Livermore National Laboratory
Full Time, Remote/Work from Home position
Listed on 2026-10-10
Job specializations:
  • Research/Development
    Data Scientist, Research Scientist, Biomedical Science, Biotech Research
Salary/Wage Range or Industry Benchmark: 6748 - 7718 USD Monthly USD 6748.00 7718.00 MONTH
Job Description & How to Apply Below
Computational Chemistry and Data Analytics - Academic Graduate Appointee

Entry Level | Full-time
Physical Life Sciences | Livermore, CA | 10/07/2026
Reference #: REF
8956J
Job Code: 710.0 Academic Graduate Appointee Ex
Organization: Physical and Life Sciences
Position Type: Academic Graduate Appointee
Security Clearance: Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: Not applicable

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

Job Description

Note: This is a one-year Academic Graduate Appointee with the possibility of extension to a maximum of two years.

We're looking for an Academic Graduate Appointee to support interdisciplinary research in computational chemistry, molecular design, data wrangling, machine learning, and high-performance data analysis by applying established computational methods to defined scientific data-analysis assignments under guidance. The role will assist with developing and maintaining reliable, reproducible workflows for managing and analyzing large-scale chemical, molecular, and biological datasets. Responsibilities include supporting the integration of simulation, experimental, and database data;

generating molecular descriptors; contributing to automated ETL pipelines; and creating tools to identify meaningful patterns. The successful candidate will collaborate across computational, experimental, and engineering disciplines to support molecular dynamics, small-molecule inhibitor discovery, AI-enabled drug discovery, and reproducible research methods. Assignments will provide opportunities to develop technical skills and professional experience under the guidance of experienced staff. This position is in the Biochemical and Biophysical Systems Group in the Biosciences and Biotechnology Division within the Physical and Life Sciences Directorate.

Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.

You will

  • Collaborate with computational chemists, computational biologists, experimental scientists, computer scientists, and engineers to support defined computational and data analytics assignments under guidance.
  • Assist in implementing and maintaining data-wrangling workflows to collect, ingest, clean, transform, standardize, and validate chemical, molecular, simulation, and biological datasets using established methods.
  • Contribute to the development and testing of ETL pipelines for high-volume scientific data, including molecular structures, simulation outputs, and molecular descriptors.
  • Assist with data from computational databases, molecular dynamics simulations, high-throughput experiments, and external sources.
  • Identify data-quality issues, including missing, duplicated, inconsistent, incomplete, or anomalous data using established data-quality practices and elevate nonroutine issues to senior team members.
  • Develop basic data visualizations and analysis toolsto identify chemical, structural, and biological trends while maintaining well-documented, version-controlled, and reproducible code for scientific data analysis.
  • Present research progress and technical results to internal team members and, as appropriate, collaborators, and other scientific audiences with guidance from senior staff while maintaining high-quality deliverables.
  • Meet all respective deadlines.
  • Perform other duties as assigned.
Qualifications
  • Ability to secure and maintain a U.S. Department of Energy Q-level security clearance, which requires U.S. citizenship and a federal background investigation.
  • Bachelor's and/or master's degree in computational chemistry, bioengineering, biomedical engineering, computational biology, bioinformatics, data science, computer science, or a related field.
  • Coursework, research, internship, or project…
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