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your career. The University is located within a beautiful historic city, home to a UNESCO World Heritage Site, and surrounded by stunning countryside. Our talented scholars and researchers from around
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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Job Description The Opportunity: The Department of Physical Sciences at the DB Campus invites applications for a Postdoctoral Researcher position in the area of Control Theory and its Applications
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
sources of gravitational radiation relevant to the LISA space mission. Research effort involves use of black hole perturbation and self-force theory, and post-Newtonian theory, to construct gravitational
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, to study novel renewable energy technologies. The candidates are expected to have a PhD degree in Chemical Engineering or related field, and have experience with optimization (theory, modeling, and tools
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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to work on some of the topics related to the GeMOS project, which include: K-dot-p theory based models of spin qubits in lateral gated quantum dots. Investigations of principles of qubit operations, noise
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Odense and is vacant from 1st February or as soon as possible thereafter. About the project The postdoc will work in the SDU Climate Elite Centre project “Mobilizing Post-Anthropocentric Climate Action: A
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular