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guidance from senior researchers. Design and execute fundamental experiments to understand energy landscapes, phase behavior, interfacial processes, and reaction pathways in multi-component systems. Design
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proteins will be screened for targeted metal binding using fluorescence, label-free, and mass spectroscopy techniques. You will: Work collaboratively in a fast-paced lab environment on a multi-disciplinary
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. Integrate fine-tuned LLMs into the existing agent-based simulation framework in HEVI-LOAD to enable agentic scenario planning and parameter tuning. Design and develop novel multi-agent reinforcement learning
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packages, including but not limited to Core Level, Infrared, and Raman Spectroscopy. Language can be anything of the candidate's preference, such as Python, Fortran etc. Leverage observations from in
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Position Description Postdoctoral Scholar - 106045 Division: AM-Applied Mathematics and Computational Research Berkeley Lab’s Center for Advanced Mathematics for Energy Research Applications (CAMERA) has a
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Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher -- Scientific Machine Learning (NESAP) to join the Workflow Readiness team as part of NERSC's