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Field
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capabilities, and particularly the Experimental Medicine Clinical Research Facility (EMCRF) (https://www.kennedy.ox.ac.uk/news/oxford-and-gsk-launch-experimental-medicine-collaboration). This will allow testing
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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neurons using multi-omics, cis-regulatory variants will be mapped onto these enhancers and then their function determined by Massively Parallel Reporter Assays (MPRA). The research will involve stem cell
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of advanced functional imaging methodologies for whole-brain mapping of neuronal activity (such as calcium functional imaging, nonlinear microscopy, and light-sheet microscopy), in parallel with monitoring
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without inducing unacceptable hot spots in healthy tissues. Parallel to developing the clinical prototype of the device, it is essential to assess the safety of the therapy by systematically investigating
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, with experience in additional languages such as Fortran considered a plus. Strong knowledge of at least one parallel programming model commonly used in HPC, such as MPI, OpenMP/OpenACC, CUDA, HIP, Kokkos
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distortions in the presence of a shallow crustal hydrothermal system at a model caldera volcano. The model will use the phase field approach and be implemented in Alya, the parallel multi-physics Computation
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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources
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parallel computing. Demonstrated hands-on experience and understanding of developing scientific data management, workflows and resource management problems. Strong problem-solving and communication skills
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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation