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live in. Your role Since 2006, the University of Luxembourg has invested in its own High-Performance Computing (HPC) facilities. Special focus was laid on developing large computing power combined with
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aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimising PIC algorithms for modern
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technologies to uncover molecular and cellular mechanisms of leukemic transformation. Collaborate with computational scientists to analyse high-dimensional data and generate mechanistic insights. Maintain
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and diazotrophs using an ultrahigh performance liquid chromatograph coupled to an Orbitrap high-resolution mass spectrometer. The approach will include non-targeted metabolomics and targeted analysis
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, preferably in Python, Fortran, Matlab or R #experience in the environment of High Performance Computing (HPC) is desirable, but not mandatory #capability to work in a team but able to formulate and carry out
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Doctoral Scientist position. This position will report to Professor Jose Polo, Lead of the Cancer Epigenetics Program at the South Australian Immunogenomics Cancer Institute (SAiGENCI) and the Inaugural
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of statistical analyses and modelling. Experience in handling and analyzing large datasets. Experience in employing high performance and cloud computing services. Knowledge in GIS. Knowledge on obtaining
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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
resources, requiring High Performance Computing (HPC) on the JUWELS HPC system and the upcoming first European Exascale supercomputer, JUPITER (both at FZJ) to facilitate exceptionally high performance for AI
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reverse phase separations Perform high-throughput synthetic chemistry, when appropriate Work in a modern synthetic chemistry lab with advanced separations capabilities The successful candidate will be
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engineering, and have a strong background in numerical analysis and scientific computing. Required qualifications include basic knowledge of numerical methods for PDEs, expertise in High Performance Computing