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Field
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parallel projects within the School. Demonstrates critical thinking skills required for interpretation of results and troubleshooting. Demonstrates strong commitment to quality and attention to detail
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maintenance of a viable research program. The candidate's research program should contribute to the areas of parallel scientific computing, with experience in several of the following areas: mesh generation
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imaging system based on the random access parallel imaging (RAP) system platform (https://doi.org/10.7554/eLife.56426 ). The RAP platform quickly collects high-contrast images in multi-well plates using
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optic cable can replace thousands of electrical links to transmit the same amount of information. As parallels to the thriving field of stretchable electronics, soft optics is emerging as a new platform
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mechanism design. The project will involve close collaboration with project teams at Imperial College London, the Edinburgh Parallel Computing Centre (EPCC) and the Luxembourg Institute of Science and
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lattice field theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging
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application development in R and Python Experience with parallel computing Author or co-author of peer-reviewed literature publications Applicants cannot have received their Ph.D. more than five years before
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Identify new applications for Machine Learning in science, engineering, and technology Develop, implement and refine ML techniques Implement parallel ML training on the High Performance Computers Engage in
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Scholar/Fellow positions is to provide individuals, who have recently (within the past 6 years) completed a doctoral degree, with a full-time program of advanced academic preparation and research training
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into algorithms for the Lov sz Local Lemma and related problems in distributed and parallel models. Research will primarily be conducted in collaboration with Dr. Davies-Peck, but successful applicants will also be