Machine Learning Postdoctoral Research Staff Member

Company Description

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 important for continued success of the Laboratory’s mission.

Pay Range

$126,720 yearly for the PDS.1 level

Job Description

We have an opening for a Postdoctoral Research Staff Member to contribute to fundamental R&D into machine learning and statistical methods to solve important problems stemming from the Laboratory's national security mission areas. You will work as part of collaborative, multidisciplinary teams to develop and deploy new machine learning methodology to support a variety of application areas, including materials science, high energy physics, predictive biology, and more. These positions are in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate.

In this roll you will

Research, design, implement, and apply advanced machine learning methods for multiple applications in a collaborative scientific environment.
Actively participate with project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex problems stemming from national security applications.
Propose and implement advanced analysis methodologies, collect and analyze data, and document results in technical reports and peer-reviewed publications.
Contribute to grant proposals and collaborate with others in a multidisciplinary team environment, including academic and industrial partners, to accomplish research goals.
Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
Perform other duties as assigned.
Qualifications
Ph.D. in Machine Learning, Statistics, Computer Science, Mathematics or a related field.
Demonstrated ability and desire to obtain substantial domain knowledge in fields of application in order to communicate effectively with subject matter experts, and to identify novel, impactful applications of machine learning.
Experience developing, implementing and applying advanced statistical or machine learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, stan, or similar.
Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software.
Advanced analytical problem-solving and decision-making skills needed to craft creative solutions and independently solve complex problems.
Experience with scientific programming in at least one high level language such as Python/R/Julia.
Experience with one of the following areas of deep learning: foundation models, robust ML, physics-constrained ML, sequential design, multimodal models, generative models, transfer learning, self-supervised learning, point cloud learning, MLOps/ML engineering.

Qualifications We Desire

Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods.
Demonstrated technical leadership in fields related to machine learning, such as mentorship or managing teams.
Experience developing or running numerical simulations of complex scientific or engineering processes.
Additional Information
All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.

Why Lawrence Livermore National Laboratory?

Flexible Benefits Package
401(k)
Relocation Assistance
Education Reimbursement Program
Flexible schedules (*depending on project needs)
Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversity
Our core beliefs - visit https://www.llnl.gov/diversity/our-values
Employee engagement - visit https://www.llnl.gov/diversity/employee-engagement

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. (This process does not apply to foreign nationals.)

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.

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.

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.