Antibody Engineering & Directed Evolution - Research Scientist

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.

We are seeking a dedicated, highly motivated ResearchScientist to lead high-impact multidisciplinary research at the interface of protein design, ultra-high-throughput experimentation, and directed evolution. The project you will join spans multiple teams in the Physical and Life Sciences Directorate, Computing, and Engineering, working on state-of-the-art approaches for antibody and protein design and optimization. We have extensive collaborations within the University of California network, and experts at Universities, National Laboratories, and industry. You will lead and champion frontier experimental R&D focused on identification, evaluation, and experimental evolution of protein-protein interactions, specifically antibody-antigen interactions, working with a diverse technical team to pioneer computational methods for in silico protein and antibody design. This role involves direct oversight of wet-lab biologists and automation engineers working to develop, automate, and scale data generation techniques to support powerful, predictive models of protein biology. This position is in the Synthetic Biology Group in the Biosciences and Biotechnology Division within the Physical and Life Sciences Directorate.

This position requires full-time on-site presence due to the nature of the work.

You will

• Develop high-throughput methods for screening protein-protein interactions to support development of AI/ML predictive models; specifically flow cytometry-based assays to characterize yeast surface display libraries (primarily antibody fragments via FACS and MACS).
• Guide the implementation and development of in vivo directed evolution capabilities at LLNL.
• Develop and maintain timelines for directed evolution campaigns, mapping dependencies between library construction, selection campaigns, and computational modeling cycles.
• Oversee a team of automation engineers translating manual data generation workflows into custom automated environments, defining target success criteria and validation benchmarks.
• Serve as the primary point of contact between the AI/ML team and the experimental team, translating between the languages and priorities of both domains to ensure clarity and productive collaboration.
• Serve as the primary point of contact with academic collaborators, coordinating meetings, joint experimental activities, data/knowledge transfer, and documentation.
• Supervise and mentor technical staff (including postdocs), providing regular feedback and guidance on experimental design, data interpretation, and program strategy.
• Present research progress and results to internal leadership and funding sponsors.
• Lead the development of manuscripts, technical reports, and patent disclosures arising from the work.
• Perform other duties as assigned.

• Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA). See Additional Information section below for details.
• Ph.D. in Biochemistry, Bioengineering, Synthetic Biology, Chemical Biology, Chemical Engineering or other relevant field.
• Significant experience withyeast display andcell sorting (FACS, MACS, custom microfluidic systems).
• Advanced knowledge ofprotein-protein interaction biology, including antibody engineering principles and biophysical characterization methods.
• Advanced inmolecular cloning and DNA library construction, sufficient to guide the work of junior team members and support troubleshooting and customization.
• Significant experience withNGS workflowsas applied to display library analysis.
• Advanced literacy in computational biology, e.g. ability to work with data in Python or R, interpret bioinformatics outputs, and engage meaningfully with purely computational colleagues.
• Significant experiencewith supervision or mentorshipof junior researchers (e.g. graduate students, postdocs, or research associates), with evidence of positive scientific and professional outcomes.
• Advancedcommunication skills, including a proven ability to convey complex experimental concepts clearly to non-experimentalists as well as non-technical stakeholders.
• Ability to operate and lead in a fast-paced, dynamic, team-based environment that prioritizes nimbleness in response to technological developments and new information.

Qualifications We Desire

• Yeast display experience, ideally including work with high-diversity libraries sizes (>105), multi-round selection campaigns, and quantitative affinity binning.
• Experience with continuous or semi-continuous directed evolutionapproaches (e.g., OrthoRep, PACE, or other in vivo hypermutation systems).
• Experience engineeringantibodies or antibody fragments(e.g. scFv, Fab, VHH) to achieve specific practical design goals.
• Experiencestructuring experimental campaigns to generate large training datasets, with an appreciation for the data quality, coverage, and format requirements critical for model development.
• Prior experiencetranslating manual experimental workflows to highly customized automated or semi-automated platform.
• Familiarity withrelevant automation environments, e.g.liquid handling platforms, robotic cell culture, or custom high-throughput systems, sufficient to support engineers building automated display and selection workflows.
• Experience managing or coordinating work across independent teams, especially academic-industry collaborations with distinct norms and expectations surrounding IP, authorship, and timelines.

Pay Range

$175,530 - $222,564 annually

This is the lowest to highest salary we in good faith believe 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.

#LI-Onsite

Position Information

This is a Flexible Term appointment, which is for a definite period not to exceed six years.If final candidate is a Career Indefinite employee, Career Indefinite status may be maintained (should funding allow).

Why Lawrence Livermore National Laboratory?

• Included in 2026Best Places to Work by Glassdoor!
• FlexibleBenefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Our values - visithttps://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 useand/or possession ofmobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area whereyou are not permitted to have a personal and/or laboratory mobile devicein your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.

Ifyou useamedical device, whichpairs with a mobile device,you must still follow the rules concerningthe mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities requireseparate 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.

CaliforniaPrivacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitlesjob 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.