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plant and other cryogenic equipment, as well as the design and planning for future EIC cryogenic systems and equipment. This position has a high level of interaction with an international and
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will be part of a team that already uses machine learning to improve online accelerator models and that develops correction algorithms for accelerator operations. This position is for a 2-year research
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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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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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adaptation, prompt engineering and benchmarking, pipeline and external resource integration (e.g., retrieval augmented generation, RAG), and various downstream analysis tasks. The position combines data
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model for behavior that reflects BNL Values and holds staff accountable. Required Knowledge, Skills, and Abilities: • PhD. in Chemistry, Materials Science, Physics, or other relevant field with 10 years
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distribution systems will be added to meet EIC requirements. The cryogenic system cools various superconducting magnets and various superconducting RF cavities throughout the EIC collider complex. Position