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. Advisers name email phone Carelyn E. Campbell carelyn.campbell@nist.gov 301.975.4920 Description First principles electronic structure methods such as density functional theory (DFT) are crucial
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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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will be secured in April 2027 and the postdoctoral position can start, at the earliest, from May/June 2027. Website for additional job details https://cpdm.univ-gustave-eiffel.fr/ Work Location(s) Number
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engineering, chemistry, physics, or a closely related field are particularly encouraged to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning
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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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strongly recommended. • High Performance Computing. • Experience with High Throughput Calculations will be valued but it is not essential. • Previous knowledge of Density Functional Theory (DFT) and
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molecular dynamics (MD), density functional theory (DFT), and quantum mechanics/molecular mechanics (QM/MM) approaches. Planned research activities will also rely on the application and further development
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, molecular, optical and chemical physics, high energy density and plasma physics, condensed matter physics, astrophysics and atmospheric sciences. Please see here for more information: https://www.unr.edu
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: https://www.uni-giessen.de/en/faculties/ggkgcsc/graduate-programmes/phdnet/phdnet Integrated internships An internship is not part of the programme. Teaching/work obligations or opportunities Members have
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apply approximation methods for interpolating electronic/phononic/thermodynamic properties of disordered crystal materials. Design and implement high-throughput density functional theory (DFT) workflows