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Field
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studies with implementation of: existing algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical.]; data management and analysis
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of collections of fluid particles distributed over a lattice is here preferred to solving non-linear PDEs. Processing a simulation in this way has some advantages. The low numerical dissipation allows
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, parallel storage systems and scientific data management. Recent research project details and outcomes can be found in computer systems conference proceedings, such as HPCA, FAST, SC, DSN, HPDC, IPDPS, and
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image processing and analysis method development. The position builds on the lab's track-record in the field of computational imaging techniques for super-resolution microscopy and image analysis
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on Earth. We have computational capabilities that are designed to process millions of tasks in parallel, allowing the entire body to function under extremely variable conditions. Our organ of vision
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pollution; perform R&D on the processing, performance and end-of-life of (biobased) polymer products. Studies can be experimental, theoretical (desk- and literature studies), or both; report the results
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opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel
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summarised by the following keywords: electrical energy, materials, innovative processes and systems, modelling and design. With over a hundred permanent staff, around a hundred PhD students and 70 other
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for large samples at ESRF ID16A using multislice tomography approaches. You will lead the development of and work with parallelized computer models to simulate how coherent waves travel through materials with
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. Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, engineers, and physicists conducting basic and applied AI/DL research