Protein Bioinformatics - Postdoctoral Researcher

LLNL • Livermore, CA

4d • $122,028 - $143,328 • Hybrid

About The Position

We have an opening for a highly motivated Postdoctoral Researcher to conduct research in computational structural biology and develop bioinformatic methods for predicting protein-protein interactions in host-pathogen systems using evolutionary and structural information. Current structure prediction tools, such as RoseTTAFold3, AlphaFold3, and ESMFold2, excel at monomeric structure prediction and at predicting known protein complexes. However, these tools struggle to identify which proteins interact and which do not. Residue-residue coevolution can be leveraged to predict interactions within organisms, but these signals are challenging to extract for interactions between organisms. You will build and leverage large protein sequence datasets to enable accurate interaction prediction and apply these methods to identify novel biological systems. You will be an integral member of an interdisciplinary, cross-institutional team working with computational biologists and experimental biologists. You will leverage existing computational tools and develop new approaches for predicting binary interactions, interaction specificity, and protein structure. You will regularly present your work and publish your research findings, including through occasional travel to collaborate with external partners and attend conferences. This position is in the Computational Engineering Division (CED), within the Engineering Directorate.

Requirements

• PhD in Life Sciences, Computational Biology, Bioinformatics, or a related technical or scientific field.
• Experience working with protein sequence and structure.
• Strong knowledge and research experience in bioinformatics and protein structure modeling.
• Ability to work independently on defined research projects, as well as a member of a team with a diverse set of scientists, engineers, and other technical and administrative staff.
• Programming experience with Python and expertise with UNIX and high-performance computing environments.
• Ability to develop independent research projects as demonstrated through publication of peer-reviewed manuscripts.
• Ability to travel as necessary.

Nice To Haves

• Strong understanding of protein bioinformatics (sequence and structure), protein structure prediction, and/or protein function prediction.
• Experience with DL structure prediction tools (RF3, AF3, ESMFold2).
• Experience in collaborating with experimental biologists.

Responsibilities

• Conduct research, and contribute to designing, analyzing, and extending sequence and structure based bioinformatic tools to develop databases that will enable protein-protein interaction predictions.
• Interpret new/understudied biological systems through protein structure prediction.
• Contribute to the development of protein sequence and structure computational frameworks and analysis tools.
• Develop structure-based distillation datasets for team members to improve ML model development.
• Collaborate with external partners (Universities, Industry, other National Laboratories) to advance computational biology simulation efforts.
• Prepare complex and detailed progress reports, written analyses, and verbal briefings to support project needs and deadlines and to present research results to sponsors.
• Independently pursue the development of new and innovative research methods relevant to the needs of Laboratory programs and/or external funding agencies.
• Contribute to proposals and statements of work.
• Publish research results in peer-reviewed scientific or technical journals and present results at external conferences, seminars, and/or technical meetings.
• Travel as needed to coordinate with research collaborators and to attend external meetings and conferences.
• Perform other duties as assigned.

Benefits

• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (depending on project needs)

What This Job Offers

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