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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
dynamics (MD) simulations of different materials families composed of Ti and C. Titanium carbides, for example, exhibit exceptional hardness, high melting point, wear and abrasion resistance, and many other
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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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, and Monte Carlo simulations. Additionally, participation in the phenomenological activities in collaboration with LHC experimentalists is anticipated. Where to apply E-mail jobs@ifj.edu.pl Requirements
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Offer Description The successful candidate will be expected to work primarily on aspects related to precision predictions for the LHC and parton-shower simulations. The project encompasses the development
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formats. Regarding the documents mentioned in point III.2.4., as an alternative to delivering a copy, the CV can also indicate the unique digital identifier of the publications, which must be of the handle
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notice. The final decision on hiring is the responsibility of the top manager of the hiring entity. Composition of the Selection Committee: President: Doctor Susana Maria Pinto de Carvalho (Associate
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in Digital Education (Department of Computer Science and Science Education, UCPH). Furhtermore, the group has a number of BA and master students associated. Later a Post Doc will join the group
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, please visit: https://dakic.univie.ac.at/ . Your future tasks: You will actively participate in research, teaching and administration. This means: You are involved in a well-funded research project
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. For additional information, please visit: https://dakic.univie.ac.at/ . Your future tasks: You will actively participate in research, teaching and administration. This means: • You are involved in a well-funded
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barrier in the planned KBS-3 concept for final disposal of spent nuclear fuel. The PhD student will develop, apply, and combine theoretical molecular dynamics (MD) simulations with experimental techniques