Additionalinformation

Additional Information

#LI-Hybrid

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years. The postdoctoral appointment is a temporary, mentored training position intended for individuals in the early stages of their postdoctoral research careers. Consistent with the structure of the program, applicants must have received their Ph.D. (or equivalent doctorate) within five years of the anticipated start date.

Why Lawrence Livermore National Laboratory?

• Included in 2026 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Our values - visit https://www.llnl.gov/inclusion/our-values

Security Clearance

None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check.

National Defense Authorization Act (NDAA)

The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112.

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request.

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.

Companydescription

Company Description

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.

Jobdescription

Job Description

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.

Interested candidates should submit a complete application that includes:

• Cover letter (1-2pgs) describing the following:
  • Research interests
  • A description of graduate work and greatest scientific accomplishments
  • How previous work (postgraduate/graduate/prior research experience) makes you a strong candidate for developing bioinformatic methods for predicting protein-protein interactions
  • What are your career goals (briefly)
  • How do you seek to approach this research area? (~1 paragraph)
• Curriculum vitae including full publication list
• Contact information for three professional references

A complete application includes a cover letter, CV, and references. Incomplete applications will not be considered.

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.

In this role, you will

• 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.

Qualifications

• 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.

Qualifications We Desire

• 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.

Pay Range

$122,028 - $143,328 Annually

This is the lowest to highest salary in good faith we would pay for this role at the time of this posting. Pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

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