Brookhaven National Laboratory is seeking to advance scientific discovery through the novel development and application of machine learning models, including large language models, multi-modal foundation models, agentic AI, embodied AI, human-AI collaboration systems, computer vision (CV) models, and natural language processing (NLP) models. This role aims to tackle challenging DOE problems using world-class computing and data resources.
Requirements
- Strong programming skills and familiarity with deep learning libraries.
- Expertise with foundation models, large vision-language models, or large-scale deep learning training.
- Experience with agentic AI, embodied AI, human-AI collaboration, surrogate models, or trustworthy AI.
- Expertise in multidisciplinary collaborations, spanning computational science, physics, chemistry, biology, or energy sciences.
- Familiarity with modern software engineering practices for scalable AI research.
Responsibilities
- Develop novel machine learning algorithms and conduct computational experiments at scale.
- Independently lead or significantly contribute to interdisciplinary projects.
- Disseminate research findings in peer-reviewed journals, conference presentations, project reports, and seminars.
- Actively contribute to proposal preparation and submission, seeking external research funding aligned with Brookhaven and DOE priorities.
- Develop and sustain collaborations with internal and external partners, including universities, national labs, and industry.
Other
- Bachelor’s degree and 8+ years, or Master’s and 6+ years, or Ph.D. with 2+ years post-PhD.
- Strong record of AI/ML research accomplishment, supported by strong publication record.
- Recognized internally and externally as an active contributor in ML research.
- Demonstrated ability to work on the interdisciplinary team.
- 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.
