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                Research Framework Programme? Horizon Europe Is the Job related to staff position within a Research Infrastructure? No Offer Description The selected candidate (M/F) will contribute to the implementation and 
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                on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training and optimizing the execution User support in 
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                ) who will develop computational electromagnetics codes for rapid characterization of the fields scattered from artificial metasurfaces. Key Responsibilities: The key responsibilities of the Research 
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                : Nonlinear dynamical systems modelling Large-scale simulations and high-performance computing Parallel programming and optimisation techniques These are high-value skills with applications across academia 
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                ) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel 
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                programming, parallel computing, and bioinformatic and statistical genetic software packages. Experience in working with genomic and proteomic data available for large extended pedigrees. License 
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                of Computer Science. The research focus of our group is on parallel computing, supercomputing, and performance tuning and optimization of advanced applications. Our team currently consists of 10 scientific and 3 
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                the process of solving increasingly complex compute- and data-intensive problems in science and engineering on high-end parallel and distributed computing platforms. The selected candidate will play an integral 
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                through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The framework of this position is an 8 
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                device efficiency. There will be an opportunity to learn the tools required for parallel computing using graphical processing units. This will be used to maximise the computational throughput to enable