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Apply Now Job ID JR101897Date posted 07/07/2025 The Condensed Matter Physics and Materials Science Division (CMPMSD)at Brookhaven National Laboratory conducts a wide-ranging research program
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Research program. The project aims to integrate a diverse suite of high-resolution observations (atmospheric, land surface, and infrastructure), diagnostic/predictive models, and civic engagement to provide
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work closely with CFN Electron Microscopy group members and computer scientists at Brookhaven. You will be professionally mentored by Dr. Judith Yang and Dr. Sooyeon Hwang and receive guidance from Prof
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of existing ones for scientific applications; (ii) Large Language Models (LLMs) and multi-modal Foundation Models (iii) Large vision-language models (VLM) and computer vision techniques; and (iv) techniques
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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
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novel genetic pathways regulating local and systemic acquired resistance, as well as growth-defense trade-offs. Using bacterial, fungal, and viral disease models, the research will focus on identifying
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by publication record). Excellent programming and computer science skills. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel ML and NLP algorithms and models and
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applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a
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investigators. Position Requirements Ph. D. in theoretical or physical chemistry, or a related field Extensive experience in one or more of the following areas: Computational modeling of homogeneous
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industry, education, and public life – including the explosion of large language models (LLMs). BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications