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. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects
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—integrating first-principles simulations with machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive
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machine learning, with demonstrated experience in developing and training neural networks for predictive modeling. Position Requirements: The successful candidate is expected to: Build and evaluate chemical
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quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational methods to study multiscale
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genetically diverse mice under a multitude of conditions, and (3) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing
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. The postdoctoral scholar will contribute to an exciting research program within the Foy Lab (www.foylab.xyz/) https://foylab.xyz/ , developing machine learning, computational, and mathematical models for improving
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applications. Research activities may involve geophysical forward modeling, AI-driven geophysical inversion, seismic monitoring and imaging, scientific machine learning, depending on the specific research focus
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commensurate with abilities and experience Type of Position Other Position Time Status Full-Time Required Education PhD in Engineering Required Related Experience see Skills / Knowledge / Abilities Required
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for postdocs. UNLV currently employs postdoctoral scholars across a wide range of disciplines. Learn more about UNLV's postdoctoral scholars. MINIMUM QUALIFICATIONS This position requires a PhD in Chemistry
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. The successful candidate will be involved in the gravitational wave astronomy research area as part of the GRAVITY research group, within the framework of the project "Ground-based Discovery Machines