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especially welcome applicants whose main strength lies in social science theory and methods and who are motivated to apply these competences to an important emerging sustainability field. Strong written and
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: - Comprehensive understanding of applied computational materials science, including electronic structure methods and molecular dynamics. - Experience with High-Performance Computing (HPC) systems and intelligent
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
in or a strong foundation in coherent sheaves, quiver varieties, affine Grassmannians and quasi-map moduli spaces. Have interest in the mathematical structures arising in string theory and
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will focus on the development of GPU-accelerated GPAW software based on density functional theory (DFT) for constant-potential calculations within a plane-wave framework. The developed software will be
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excellence, as evidenced by a strong publication record in one or more of the following areas: random matrix theory, stochastic processes, neural networks, machine learning, and sparse data structures
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physics and electromagnetic (EM) theory/modeling, at the Electrical and Computer Engineering Department, and in collaboration with the Applied Mathematics Department, Santa Clara University. This is an in
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quite new within the field of computer vision. The neuromorphic design allows for a much higher acquisition frequency but most and foremost much longer acquisition time spans. This makes it ideal
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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
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that matter to society and impact the Maine economy. Postdocs will receive formal and structured mentoring on topics including mentor/mentee research relationship, technology transfer, and proposal development