Data Science - Postdoctoral Researcher

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 dedicated to fostering a culture that values individuals, talents, partnerships, ideas, experiences, and different perspectives, recognizing their importance to the continued success of the Laboratory's mission.

Pay Range

$143,328 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.

Job Description

We have an opening for a Data Science
Postdoctoral Researcher to perform research in multi-objective reinforcement learning as applied to physics and engineering problems, such as may be used in the protection of critical infrastructure. This may require the development of numerical linear algebra techniques in order to achieve efficient computation, as well as neural network and data compression to enable models to run on constrained edge hardware. In addition, statistical techniques and stochastic computing methods are frequently employed to enable reasoning and learning under uncertainty.

You will support ongoing projects by developing capabilities to solve real-world problems aimed at improving the safety, reliability, and efficiency of our nation's critical infrastructure. This position is in the Center for Applied Scientific Computing (CASC) within the Computation Directorate.

In this role you will

• Research and develop reinforcement learning techniques to solve physics and engineering problems focused on the protection of critical infrastructure.
• Research and develop neural network compression and efficiency-enhancing approaches to enable effective use in constrained environments.
• Research and develop multiresolution data compression and visualization techniques to enable analysis of complex data.
• Develop high-quality software that solves complex machine learning problems that is extensible and maintainable by downstream users and developers.
• Deploy software on real-world devices to evaluate novel techniques in real-world settings.
• Develop and test algorithms and software in practical settings taking real-world limitations under consideration.
• Interact with engineers and other stakeholders in the space to understand those practical, real-world limitations.
• Pursue independent (but complementary) research interests and being able to interact with team members internally and externally.
• Publish research results in external peer-reviewed scientific journals and participate in conferences and workshops.
• Present formal and informal overview of research progress at group meetings.
• Participate in existing division collaborations and alliances with academia and industry.
• Perform other duties as assigned.

• PhD in Computer Science, Mathematics, or related field.
• Research experience in machine learning and reinforcement learning.
• Research experience in optimization or numerical linear algebra.
• Research experience in neural network compression, efficiency, or distillation.
• Ability to conduct high quality research and to develop implementations of sophisticated algorithms to evaluate the results.
• Experience programming in Python and/or C++.
• Proficient verbal and written communication skills necessary to interact with members of a research team, author technical and scientific reports and papers, and deliver technical presentations.
• Demonstrated publication record in peer-reviewed journals and/or conferences.
• Strong decision-making skills necessary to independently solve complex research problems.

• Experience in developing parallel or high-performance software.
• Experience developing leveraging software design principles to build extensible and maintainable software.
• Experience in an engineering area such as power grid analysis.

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.

• 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 - visithttps://(Use the "Apply for this Job" box below).-values

None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification…