Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States' security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory's mission.

Pay Range:

$191,220 - $245,544 Annually

Please note that the pay range information is a general guideline only. Many factors are taken into consideration when setting starting pay including education, experience, the external labor market, and internal equity.

The Generative Unconstrained Intelligent Drug Engineering (GUIDE) project has an opening for a Senior bioengineer who is responsible for the efficient, smooth, and effective management of a team and simulation- and machine-learning-driven computational pipeline to redesign antibodies. GUIDE is an exciting and fast-paced program combining predictive computational modeling, machine learning, and experimental biology to develop medical countermeasures for the Department of Defense (DoD). The ideal candidate will have a breadth of protein engineering experience to manage a multi-disciplinary team with expertise in machine learning, molecular simulation, optimization, and structural and protein biology. The candidate will apply in-house computational tools in rigorous campaigns to redesign specific antibodies so that they are more potent, broadly neutralizing and/or developable as a prophylactic or therapeutic antibodies.

The candidate will elicit highly technical information required to formulate antibody redesign goals; to facilitate the creation and joint understanding of these goals via a network of colleagues with differing technical expertise; to communicate and ensure ongoing consensus on these goals; and to continually guide alignment of effort to them. The candidate will manage all aspects of the computational redesign campaign, and, as such, requires deep technical expertise in protein and structural biology/bioegineering or machine learning and simulation tools, and a willingness to gain complementary expertise.

The candidate needs to be comfortable with a flexible technical approach, willing to re-compose existing tools and workflows to execute the job at hand, and to lead others toward the execution of the work.

The candidate must be team-oriented and have leadership experience and resilience to drive the work forward while maintaining a balanced view that serves the needs of the GUIDE program and its durable capabilities.

You will

• Research, analyze, develop, document, and execute a technical plan for each antibody redesign campaign, including determination of appropriate data, tools, and team members to support the effort.
• Manage all aspects of the computational redesign campaign from start-to-finish.
• Actively lead project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex antibody redesign campaigns.
• Propose and implement advanced analysis methodologies, analyze data, and document research through presentations and peer-reviewed journal articles and contribute to identifying future research directions and proposals that will secure future projects in the field.
• Foster collaboration between computational and biological staff to improve the speed and accuracy of computational antibody redesign campaigns.
• Direct technical activities, as needed, in support of new capability development and technical problem solving.
• Establish ,maintain and ensure quality standards for project deliverables and guide project teams through antibody redesign processes.
• Perform other duties as assigned.

• Ability to secure and maintain a U.S. DOE Q-level security clearance, which requires U.S. Citizenship.
• Advanced degree in Computational Biology, Machine Learning, Statistics, Computer Science, Mathematics or a related field.
• Demonstrated technical leadership in leading multidisciplinary teams in fields related to machine learning, such as mentorship or team management.
• Expert verbal and written communication skills as reflected in effectivepresentations at seminars, meetings and/or teaching lectures.
• Initiative and interpersonal skills with desire and ability to work in a collaborative, multidisciplinary team environment.

Additional Qualifications We Desire

• A good-to-strong understanding of bioinformatics, protein biology, antibody development, and pathogen science, especially virology
• Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflow

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Career Indefinite position, open to Lab employees and external candidates.

Why Lawrence Livermore National Laboratory?

• Included in 2024 Best Places to Work by Glassdoor!
• FlexibleBenefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Inclusion, Diversity, Equity and Accountability (IDEA) - visithttps://www.llnl.gov/diversity
• Our core beliefs - visithttps://www.llnl.gov/diversity/our-values
• Employee engagement - visithttps://www.llnl.gov/diversity/employee-engagement

Security Clearance

This position requires a Department of Energy (DOE) Q-level clearance.If you are selected, wewill initiate a Federal background investigation to determine if youmeet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship.

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.

Pre-Placement Medical Exam

A job related pre-placement medical examination may be required.

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.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.

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.

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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.