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in high-performance computing using MPI. Experience in GPU programming using OpenACC, CUDA, CUDA-Fortran, Julia, or related tools. Experience in CFD meshing software. TU Delft (Delft University
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environment, which brings together more than 400 researchers across disciplines. The collaboration provides access to substantial computational resources (GPU nodes), advanced high-throughput instruments
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reports to the Director of Advanced Research Computing, Security, and Information Management (ARCSIM) and will help support the needs of the UMaine research community and its collaborators by enabling and
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signal processing and/or survey datasets. ML & AI techniques and applications. HPC and orchestration of scientific data processing workflows. Parallel computing (GPU & CPU). good software engineering
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Abilities: Experienced in heterogenous computing with GPU accelerators using one of the programming models: CUDA, HIP, SYCL, Kokkos, OpenMP, OpenACC and similar. Familiar with distributed parallel computing
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Classification Title: Lecturer/Assistant Instructional Professor Classification Minimum Requirements: PhD degree in Geography, Geographic Information Science, Data or Computer Sciences, or a related
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. in physics, bioengineering, or a closely related field. Preferred Qualifications Extensive experience in Monte Carlo simulation, GPU-based parallel computing, and image reconstruction techniques
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including heterogeneous accelerator devices such as GPUs, DSPs or FPGAs, requiring software to cope with concurrent and parallel synchronous and asynchronous computation.; The emergence of connected
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together more than 400 researchers across disciplines. The collaboration provides access to substantial computational resources (GPU nodes), advanced high-throughput instruments (including a FACS, mass
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at the Department of Informatics. Position as Postdoctoral Research Fellow available at the Department for Informatics with the research group Digital Signal Processing and Image Analysis (https://www.mn.uio.no/ifi