Senior Scientific Engineering Associate

Lawrence Berkeley National Lab’s (LBNL) Nuclear Science Division (NSD) has an opening for a Senior Scientific Engineering Associate to join the team of scientific staff from several programs.

A variety of soft skills and experience may be required for the following role Please ensure you check the overview below carefully.

In this exciting role, you will be a part of the Machine Learning / Artificial Intelligence (ML / AI) project focused on the optimal operation of the Versatile ECR ion source for Nuclear Science (VENUS) ion source.

You will take a central role in the application of machine learning techniques to address the challenges of optimization of the world-leading superconducting ECR ion source VENUS.

What You Will Do :

Participate in the development of a machine learning framework that will allow for the computer driven control and analysis of VENUS.

This framework will be made generalizable enough to be applied to other Department of Energy accelerator-related systems.

• Develop, test, and optimize machine learning and large data analytics frameworks so they may be used reliably, with a focus on the optimized operation of VENUS.
• Collaborate and partner with scientists, technicians, and engineers, on the safe operation and basic scientific principles of VENUS.
• Present results at collaboration meetings, seminars, workshops and conferences and publish refereed journals.

What is Required :

• BS. in Physics, Machine Learning, Computer Science or related discipline.
• Experience with data analysis and computer programming in Python and / or C / C++, and a familiarity with machine learning techniques.
• A demonstrated ability to perform research individually and as part of a research group.
• Excellent verbal and written communication skills and strong organizational, analytical, and interpersonal skills.
• Ability to work effectively with staff at all levels with the Nuclear Science Division.
• Demonstrated outstanding data analysis / programming skills and proficiency in C / C++ and Python.

Desired Qualifications :

MS. or Ph.D. in Physics, Machine Learning, Computer Science or related discipline.

Notes :

• For full consideration, please apply by October 9, 2025.
• This is a full-time 1 year, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
• This position is expected to pay $99,000.00-$123,768.00, which fits within the full salary range of $99,000.00-$167,100.

00 for the N50.2. Salary for this position will be commensurate with the final candidate’s qualification and experience, including skills, knowledge, relevant education, certifications, and aligned with the internal peer group.

• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position.
• Work will be primarily performed at : Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

Learn About Us :

Berkeley Lab (LBNL) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe.

Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 16 Nobel prizes. The University of California manages Berkeley Lab for the U.

S. Department of Energy’s Office of Science.

Working at Berkeley Lab has many rewards including a competitive compensation program, excellent health and welfare programs, a retirement program that is second to none, and outstanding development opportunities.

Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA) and strives to continue building community with these shared values and commitments.

Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab’s mission of leading scientific discovery, inclusion, and professionalism.

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