Machine Learning - Postdoctoral Researcher

Mid-Senior Level | Full-time Information Technology/Computing | Livermore, CA | 03/20/2026 Reference #: REF7351Z Job Code: PDS.1 Post-Dr Research Staff 1 Organization: Computing Position Type: Post Doctoral Security Clearance: None/Position does not require US citizenship (assignments longer than 179 days require a federal background investigation) Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana) Medical Exam: Not applicable Apply Now 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. Job Description We’re looking for a Machine Learning Postdoctoral Researcher to contribute to fundamental R&D in machine learning and statistical methods in support of different projects related to AI Safety & Security, Foundation Models in areas such as material science or bio assurance, and uncertainty quantification for deep learning models. These will be interdisciplinary projects that aim to combine state-of-the-art machine learning models with various science objectives. Examples are multi-modal sequence-to-sequence models for molecules and chemical reactions or combine large language models with other modalities. Furthermore, you will develop methods to improve safety and trustworthiness of these models. This position will be in the Machine Intelligence Group in the Center for Applied Scientific Computing (CASC) Division within the LLNL Computing Directorate. Responsibilities 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 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. Recent Ph.D. in Machine Learning, Optimization, Computer Science, Mathematics or a related field. Demonstrated ability and desire to obtain substantial domain knowledge in fields of application to enable effective communication 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, or similar as evidence through medium to large scale deep learning models and experiments. Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software in relevant venues (NeurIPS, ICML, ICLR, CVPR, AAAI, AISTATS, UAI, KDD, JMLR, Nature etc.). Experience with scientific programming in the Python ecosystem as evidence through software artifacts, such as deep learning models, workflows, simulations, or similar. Experience with one or more of the following areas of deep learning: large language models, graph neural networks, multimodal models, generative models, robustness, explainable AI. Desired Qualifications Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflows. Demonstrated technical leadership in fields related to machine learning, such as mentorship or managing teams. Experience or interest in scientific applications, such as material science, climate science, etc. Pay Range $138,480 Annually 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. Security and Eligibility 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. 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. 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. Equal 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. #J-18808-Ljbffr Lawrence Livermore National Laboratory