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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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of the Research Project(s): The goal of our research is to develop vaccines and therapeutics targeting human pathogens. Duties and Responsibilities: 20% Structure-based and machine-learning immunogen design for
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to develop generative AI methods for nanoparticle drug delivery design, at the intersection of machine learning, explainability, and pharmaceutical nanotechnology. Job description We are looking for a
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 24 hours ago
the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our
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and simulation Prior experience with particle accelerators and/or FELs is highly desirable Familiarity with machine learning techniques is a plus but not necessary Excellent command of English is
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by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision
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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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modeling approaches-including machine learning (ML), hydrologic and energy systems simulations, and scenario forecasting-to evaluate dynamic energy-water futures and resilience strategies for diverse Idaho
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for machine learning models to optimise membrane properties, structure, and fabrication. The fellow will play a key role in the experimental part of the project, including: Preparation and characterisation