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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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You will be working in a larger research and development project in parallel, distributed and heterogeneous computing. The project work can, under certain circumstances, be combined with an internal
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hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied
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reviewed • Understand the product thoroughly; Analyse, design and develop functionalities based on product requirements • Work with researchers to implement and develop parallel and distributed systems
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projects will work towards this goal. PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://www.hvl.no/en
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Hint Due to serious budgetary cuts there will be no further calls for the German Chancellor Fellowship Programme. • The fellowships granted to the current cohort of Federal Chancellor Fellows 2023
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optimisation, distributed-parallel-GPU optimisation (e.g. pagmo2), Taylor-based numerical integration of ODEs (e.g. heyoka), differential algebra and high order automated differentiation (audi), quantum