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) with expertise and interest in Large Language Models (LLM) for Energy Environmental Research and Applications. The researcher(s) will work with the principal investigator and team to develop, fine tune
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operations. Building and applying foundation models and surrogate models to speed analysis and optimize performance. Designing and maintaining digital twins of fusion devices, including autonomous control
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to lead an investigation exploring the ability of recently developed global earth system models to simulate coastal sea level across sub-annual timescales. This work will leverage a suite of coupled models
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partner management, or other types of relationship management); experience with a range of different institutional donor and individual giving models a plus. Ability to build strong relationships with
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spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025, and will remain open until excellent fits are found.The
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between climate dynamics and marine biogeochemistry is also essential. The successful candidate will demonstrate proficiency in numerical modeling and statistical methodologies for interpreting in-situ and
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skillsExpertise in Generative AI: Strong background in machine learning, with specific experience in Large Language Models (LLMs), and Vision-Language Models (VLMs)Excellent programming skills (Python is required
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advanced artificial intelligence / machine learning (AI/ML) solutions for fusion science and operations. Building and applying foundation models and surrogate models to speed analysis and optimize
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), seeks a postdoctoral or more senior research scientist to lead an investigation exploring the ability of recently developed global earth system models to simulate coastal sea level across sub-annual
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the context of simulation and modeling. Any experience programming with Julia would be a bonus, although it is not necessary. Candidates should be interested in applying computational techniques to the study of