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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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candidates should have a major in electrical engineering, computer science, or applied mathematics. A background in electric power systems modeling and simulation and data analytics and machine learning
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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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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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simulation, AI based detector design optimization, streaming computing model development, production, distributed computing and workflow management, software infrastructure, particle ID, tracking
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Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a wide range of material parameters. The CFN develops and utilizes
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and imaging x-ray tools, supported by computational resources for high-throughput analysis and modeling. The program’s scientific focus is to understand and optimize the structural and chemical features
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the large language models, and multi-modal Foundation Models; ML models for computer vision (CV) and natural language processing (NLP) related tasks; and techniques applied to the scientific discovery, i.e
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, detailed 3D modeling and design, design and safety reviews Work closely with scientific staff as well as other engineering groups to develop solutions to complex problems and integration issues Prepare cost
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hands-on with mechanical equipment, and collaborating with a team to develop and build unique equipment. Demonstrated ability with 3D Computer Aided Design modeling software. Ability to perform mechanical