PostDoc – Machine Learning

The Artificial Intelligence Learning department of the Computing and Data Sciences (CDS) directorate at Brookhaven National Laboratory (BNL) invites exceptional candidates to apply for a post-doctoral research associate position in machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in concert with collaborators working on diverse scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) development of novel machine learning models and adaptation of existing approaches for scientific applications; (ii) Large Language Models (LLMs) and multi-modal foundation Models (iii) Agentic AI techniques for scientific domains; and (iv) techniques supporting end-users of applied ML methods.

The position provides access to world-class computing resources, such as the BNL Institutional Cluster and DOE leadership computing facilities. Access to these platforms will allow computing at scale, and together with access to unique data sources, will ensure that the successful candidate has the necessary resources to solve challenging DOE problems of interest. The successful candidate will join a growing research group with diverse expertise and projects spanning the full breadth of BNL’s and the DOE’s missions. This post-doc position presents a unique chance to conduct interdisciplinary collaborative research in BNL programs.

Essential Duties and Responsibilities:

• Conduct research in ML, foundation models and agentic AI models for various problems relating to scientific discovery.
• Work in interdisciplinary collaborations with subject matter experts on various aspects of scientific data generation and processing and methods evaluation.
• Formulate high-quality research ideas and directions in collaboration with mentors in the department.
• Communicate research progress, challenges, and achievements, and engage within and beyond the department on new potential collaborations.

Position Requirements

Required Knowledge, Skills, and Abilities:
 

• Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics) awarded within the past 5 years.
• Strong theoretical understanding and practical experience in machine learning, foundation models, and agentic AI technique.
• Demonstrated publication record in machine learning field.
• Excellent programming and computer science skills.

Preferred Knowledge, Skills, And Abilities:

• Practical experience developing novel ML, foundation model, or agentic AI models.
• Experience with state-of-the-art foundation models and agentic AI models.
• Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization.
• Experience in multi-modality data analysis (e.g., image, video, text).
• Experience working in multidisciplinary collaborations.

Other Information:

• Initial 2-year term appointment subject to renewal contingent on performance and funding
• Candidates must have received a Ph.D. by the commencement of employment. 
• BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness, or other life-changing events
• This is a fully onsite position located at BNL in Upton, NY

Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $71900 - $119000 / year. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group.