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Field
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WEKA, VAST, GPFS, BGFS, CEPH. Experience with installing and supporting: Open source and commercial research related software, Python, R, Matlab, Mathworks, Julia, Ansys, Intel, nVidia CUDA and GCC
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-performance computing Experience in design of computational pipelines for large-scale imaging Experience with programming languages and scripting methods (i.e. Python, MATLAB, C++, CUDA, Bash, and/or SQL) and
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one of the above fields Very good expertise in the programming languages Python and C/C++, the numba library, and in applying parallelization techniques using GPU programming (CUDA/OpenCL) and MPI
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MPI, OpenMP, CUDA or OpenACC. Familiarity with scientific software stacks or domain-specific tools (e.g., BWA, Samtools, GATK, Gromacs). Experience supporting research involving regulated data (e.g
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CUDA. What we can offer you: An opportunity to play a key role in a multidisciplinary team driving innovation in the deployment of deep neural network (DNN) models across a continuum of edge-to-cloud
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, successful experience with parallel programming using languages such as OpenCL and/or CUDA 7. Demonstrated, successful experience with source code version control systems such as Git, Subversion, or similar 8
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) environments 6. Demonstrated, successful experience with parallel programming using languages such as OpenCL and/or CUDA 7. Demonstrated, successful experience with source code version control systems such as
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., DeepSpeed, FSDP, Ray, or MPI-based systems). Familiarity with GPU-accelerated computing (e.g., CUDA, NVIDIA ecosystem). Preferred Qualifications Education: No additional education beyond what is stated in
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-based systems). Familiarity with GPU-accelerated computing (e.g., CUDA, NVIDIA ecosystem). Preferred Qualifications Education: No additional education beyond what is stated in the Required Qualifications
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be an expert within object oriented fortran, CUDA, HIP, build systems such as CMAKE and Autotools, the Github CI/CD platform and schedulers such as SLURM and LSF10. The candidate should hold a MSc in