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transformative solutions to compelling problems in energy and security. Our diverse capabilities span a broad range of scientific and engineering disciplines, enabling the laboratory to explore fundamental science
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computational foundations of that capability and help bridge the gap between Bayes theory and practical application: knowledge integration, developing robust likelihood frameworks, sampler behavior for long
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of integrated data and AI workflows that span data acquisition, modeling, and decision-making, including deployment at the edge and across distributed systems. You will have access to extensive experimental and
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distributed codes using MPI, OpenMP, CUDA, ROCm, and related HPC technologies while bridging theoretical AI models with real hardware constraints. Cross‑Paradigm Integration(new optional emphasis): Explore how
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of complex biosystems. The successful candidate will also contribute to efforts that bridge molecular, cellular, and systems-level modeling, with growing relevance to emerging paradigms such as whole-cell
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. Focus will largely be in developing and deploying such AI/ML algorithms, closely collaborating with theorists and experimentalists to realize physics- models and/or physics-aware ML-models that can bridge
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AI/ML surrogate models for inverse design of new materials and processes, incorporating simulated and experimental multi-modal datasets. Develop AI/ML approaches to bridge length- and time-scales in