Postdoctoral Research Associate – AI/ML for Biological Sciences

Brookhaven National Laboratory’s Computing and Data Sciences (CDS) Directorate seeks a Postdoctoral Research Associate – AI/ML for Biological Science for an on-site position in the AI Department.

The successful candidate will contribute to interdisciplinary research projects at the intersection of artificial intelligence, machine learning, and domain science, with a particular emphasis on biology.

This position is intended for candidates with strong expertise in AI/ML, data science, and computational analysis, who are interested in applying advanced computational methods to biological data and scientific problems.

Position Description:

The Postdoctoral Research Associate will develop and apply AI/ML and data-driven approaches to support biological research projects within the CDS AI Department. The selected candidate will work closely with computational scientists, AI researchers, and domain collaborators to analyze complex biological datasets, build or adapt computational models, and help advance data-enabled discovery in biology. The ideal candidate will have strong training in machine learning, artificial intelligence, statistical modeling, or related computational fields, along with sufficient background or interest in biological applications. 

Essential Duties and Responsibilities:

• Conduct research in artificial intelligence, machine learning, and data science in support of biology-related projects.
• Collaborate with AI researchers, computational scientists, and biology domain experts to translate scientific questions into effective computational workflows.
• Evaluate model performance, interpret results, and contribute to reproducible analysis pipelines and research software.
• Document methods and results and contribute to manuscripts, reports, presentations, and other project deliverables.
• Participate in interdisciplinary team science.

Required Knowledge, Skills, and Abilities:

• Ph.D. in computer science, statistics, applied mathematics, biology, or a closely related field.
• Demonstrated expertise in AI/ML, statistical learning, or advanced data analytics.
• Experience developing, applying, or evaluating novel machine learning or data-driven methods on complex real-world datasets.
• Ability to work effectively in a collaborative, interdisciplinary research environment.
• Strong track record of research productivity, demonstrated in peer-reviewed publications or equivalent research outputs.
• Demonstrated commitment to working safely, acting ethically, and taking personal accountability for operational excellence.

Preferred Knowledge, Skills, and Abilities:

• Familiarity with computational biology, bioinformatics, or biological data science concepts and workflows.
• Computational skills, including experience with programming/scripting for large-scale data analysis and reproducible research workflows.
• Experience using biological software tools, workflows, and databases.
• Experience with deep learning, large language models (LLMs), protein language models (PLMs), or related generative AI methods for scientific or biological applications.
• Proven exposure to model development, fine-tuning, evaluation, benchmarking, or deployment in modern AI/ML environments.
• Worked with heterogeneous, multimodal, or large-scale scientific datasets.
• Experience contributing to reusable analysis workflows, scientific software, open-source projects, or collaborative codebases.
• Familiarity with agentic AI systems, AI-assisted scientific workflows, or tool-using autonomous or semi-autonomous AI frameworks.

Additional Information:

• This is an on-site position based at Brookhaven National Laboratory in Upton, New York.
• This position has an initial 2-year term, with the possibility of renewal contingent on performance and funding availability.
• Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $ $71,900 - $119,000/ year. You will be placed at the level and salary commensurate with your experience.  Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group.
• 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.
• Candidates must have received a Ph.D. by the commencement of employment.  

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

Brookhaven National Laboratory requires all non-badged personnel including visitors to produce a REAL-ID or REAL-ID compliant documentation to access Brookhaven National Laboratory – view more information at www.bnl.gov/real-id.  This is due to nationwide identification requirements for federal site access as required by the federal REAL ID Act.  Those not in possession of a REAL ID-compliant document will not be permitted to access the site which includes access to the Laboratory for interviews. 

As a U.S. Department of Energy laboratory, Brookhaven National Laboratory requires employees to obtain and maintain a DOE Uncleared Personal Identity Verification (UPIV) credential in accordance with Homeland Security Presidential Directive 12 (HSPD-12) requirements. The credentialing process is completed as part of onboarding and enables access to DOE facilities and information systems. As a condition of employment, the selected candidate must be able to obtain and maintain a UPIV credential. These requirements are established under DOE Order 206.2 Chg. 2, Identity, Credential, and Access Management (ICAM- Identity, Credential, and Access Management (ICAM)), and DOE Order 473.1A- Physical Protection Program- Physical Protection Program.

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

Guided by our core values of integrity, responsibility, innovation, respect, and teamwork, Brookhaven Science Associates is an Equal Employment Opportunity Employer-Vets/Disabled. We are committed to fostering a respectful and collaborative environment that fuels scientific discovery. We consider all qualified applicants without regard to any characteristic protected by law. All qualified individuals are encouraged to apply. 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