Brookhaven National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review more information at BNL | Benefits Program

The AI/ML Department of Computational Science Initiative (CSI) 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) novel development of deep learning ML models and adaptation of existing ones for scientific and security applications; (ii) ML model optimization for inference speed and deployment for real-time analysis; and (iii) AI model training for analog in-memory computing.

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 with a highly competitive salary.

Essential Duties and Responsibilities:

• Conduct research and develop novel AI/ML algorithms and solutions.
• Disseminate research findings in publications, posters, project reports, presentations, and other related media.

• Work in interdisciplinary collaborations with subject matter experts.
• Communicate research progress, challenges and achievements, and engage within and beyond the group on new potential collaborations.
• May formulate own high-quality research ideas and directions pertaining to the DOE mission.
• May contribute to preparing funding proposals.

Position Requirements:

Required Knowledge, Skills, and Abilities:

• Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics, physics) awarded within the last 5 years.
• Strong theoretical understanding and practical experience in deep learning-based machine learning.
• Strong research experience (e.g. evidenced by publication record).
• Excellent programming skills and in-depth computer science knowledge.

Preferred Knowledge, Skills, and Abilities:

• Practical experience developing novel AI/ML algorithms and models.
• Knowledge about hardware architectures, compilers, neural network optimization.
• Basic knowledge of integrated circuit design, including digital simulation and logic synthesis.
• methods, and other related topics pertaining to fast AI model inference.
• Experience working in multidisciplinary collaborations.
• Effective communication skills.

Compensation:

• Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $70200 - $116200 / year. Salary offers will be commensurate with the final candidate's qualification, education and experience and considered with the internal peer group.

Other Information:

• Initial 2-year term appointment subject to renewal contingent on performance and funding
• 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

About Us

Brookhaven National Laboratory (www.bnl.gov) delivers discovery science and transformative technology to power and secure the nation's future. Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The Lab is primarily supported by the U.S. Department of Energy's (DOE) Office of Science. Brookhaven Science Associates (BSA) operates and manages the Laboratory for DOE. BSA is a partnership between Battelle and The Research Foundation for the State University of New York on behalf of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans at Brookhaven National Laboratory.

Equal Opportunity/Affirmative Action Employer

Brookhaven Science Associates is an equal opportunity employer that values inclusion and diversity at our Lab. We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class. BSA takes affirmative action in support of its policy and to advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. *VEVRAA Federal Contractor

BSA employees are subject to restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation at the time of hire for review by Brookhaven. The full text of the Order may be found at: https://www.directives.doe.gov/directives-documents/400-series/0486.1-BOrder-a/@@images/file