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Field
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-edge research in transportation artificial intelligence, digital twins, intelligent transportation systems, cooperative driving automation, and energy-efficient mobility. The selected candidates will
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few-shot adaptation. The project is rooted in scientific machine learning, with biological imaging and biophysical simulation as driving testbeds. We work with data that range from chromatin
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environment, the postdoctoral researcher will develop and apply advanced simulation techniques, and data-driven approaches to explore complex biophysical phenomena at the cell membrane. This role
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environment, the postdoctoral researcher will develop and apply advanced simulation techniques, and data-driven approaches to explore complex biophysical phenomena at the cell membrane. This role
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environment, the postdoctoral researcher will develop and apply advanced simulation techniques, and data-driven approaches to explore complex biophysical phenomena at the cell membrane. This role
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Associate in the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials
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Associate in the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials
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, orchestration, and trust, and their results must connect into one coherent system. You will make that possible through interface-first integration: a shared interface schema, a co-simulation framework, and
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Associate in the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials
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related field plus two (2) years of post-degree experience in computational systems modeling, simulation, and analytics; OR Master’s degree in computational biology, systems biology, bioinformatics