The Machine Learning Group within Brookhaven National Laboratory’s Computational Science Initiative (CSI) invites exceptional candidates to apply foran Assistant/Associate Computational Scientist (RS3/4) position focused on 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 Brookhaven Lab and the Department of Energy (DOE). Topics of particular interest include novel development of deep learning ML models and adaptation of existing ones for scientific and security applications; ML models for natural language processing (NLP) and computer vision (CV), e.g., Large Language Models (LLMs) and multi-modal, multitask Foundation Models; and techniques supporting stakeholders and end users of applied ML methods, such as uncertainty quantification (UQ), interpretability and explainability for artificial intelligence (XAI), and responsible AI.

This position provides access to world-class computing and data resources, such as Brookhaven Lab’s Institutional Cluster and DOE leadership computing facilities. These platforms afford computing at scale, as well as access to unique data sources, ensuring the successful candidate will have the necessary tools to tackle challenging DOE problems of interest. In addition, the successful candidate will join a growing research group with diverse expertise and projects that span laboratory-level and nationally concerned DOE missions. This research staff position presents a distinct opportunity to conduct interdisciplinary collaborative research at Brookhaven Lab with a highly competitive salary.

Position Description:

Essential Duties and Responsibilities:

• Develop novel algorithms and solutions and contribute to project success.
• Disseminate research findings in publications, posters, project reports, presentations, and other related media.
• Conceptualize and promote new research ideas.
• Effectively communicate with team members and collaborators from other scientific domains within and beyond Brookhaven Lab.
• May function as a technical leader role in a large project or a project leader role in small projects.
• May need to coordinate efforts within a large project or among multiple small projects.
• May contribute to or lead preparing funding proposals.

Position Requirements:

Required Knowledge, Skills, and Abilities:

• Bachelor’s degree and eight or more (8+) years of experience or Master’s degree and six or more (6+) years of experience or Doctorate and two or more (+2) years post-PhD; experience in computer science or related fields (e.g., applied mathematics, statistics, physics).
• A strong publication track record.
• Excellent programming skills and computer science knowledge.
• Familiar with deep learning libraries.
• Effective written and oral communication capabilities.
• Ability to work closely and effectively with researchers from different backgrounds.

Preferred Knowledge, Skills, and Abilities:

• Bachelor’s degree and twelve or more (12+) years of experience or Master’s degree and nine or more (9+) years of experience or Doctorate and six or more (6+) years post-PhD; experience in computer science or related fields (e.g., applied mathematics, statistics, physics).
• Experience in preparing proposals and project management.
• Experience working as part of multidisciplinary scientific collaborations.
• Research experience in large language models and/or computer vision models.
• Knowledge about large-scale model training in a distributed environment.
• Commitment to responsible AI (e.g., robust learning, explainable AI, uncertainty quantification, reproducible and trustworthy AI).

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Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. This is a multi-level role and the full salary range for this position is $98650 - $179350 / 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.