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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 23 hours ago
USNH Employees should apply within Workday through the Jobs Hub app The research position is within the broad area of biophysics, structural modeling, and molecular dynamics (MD) simulations
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Job Description Declaration of interest regarding PhD project: Department of Molecular Medicine at SDU is looking for applicants for a PhD scholarship within the field of biomarker and therapeutic
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or other technical applications—often represent the critical point where materials and molecular functionality is determined. The research task involves establishing a research direction involving advanced
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
Temporary contract | 14 + 22 + 14 months | Belvaux Are you fascinated by data-driven atomistic simulations for materials science? So are we! Come and join us. We seek a highly motivated and capable
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Tasks and responsibilities: The PhD position is framed within the MAIAMI project. The student will work on DFT and molecular dynamics simulations, generating structural and electronic descriptors
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apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular dynamics (MD) simulations
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will employ advanced molecular, cellular, and systems biology methods and tools. The main goal of the project is to expand our understanding of the intersection of hypothalamic-pituitary communication
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-QM methodology on molecule-metal interfaces by simulating surface catalytic reactions and spectroscopy. This project will directly support molecular optoelectronics design and catalyst design research
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build stable, self-healing interphases for long-life cycling. Working jointly between the University of Edinburgh and Heriot-Watt University, you will combine: Molecular simulations (to see how different
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principles molecular dynamics simulations. You will contribute to the development of novel work flows as well as to the training, testing and application of latest neural network methodologies. Applications