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Field
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successful applicant will join Andrej Prsa’s research team and work on cutting-edge theoretical and observational aspects of binary and multiple stellar populations. In parallel, the applicant will teach
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with implementation machine learning methods and development of high-performance scientific software with CPU and GPU parallelization, knowledge of LAMMPS. 2. Computational investigations of catalytic
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will join Andrej Prsa’s research team and work on the PHOEBE code , advancing our understanding of the processes in contact binary stars. In parallel, the applicant will be given an opportunity to teach
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model is employed to forecast renewable energy availability, providing crucial insights for the design optimization process. The ML-assisted operation tackles the dynamic optimization of parallel energy