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MPI Understanding of plasma physics and computational plasma physics Experience with Particle-In-Cell (PIC) code development and kinetic models Experience in high-performance computing (HPC) and/or GPU
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fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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dynamic research environments, exhaustive training opportunities and institutional collaborations. The PhD candidate will benefit from the computational resources available at CEPAM (GPU servers). He/She
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will be considered a plus: Data analysis libraries such as Dask Knowledge and experience with Python, Fortran and/or GPU computing HPC and parallel libraries such as OpenMP and MPI HPC parallel IO