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++, Rust, or similar languages. CUDA experience is a plus. Passion for interdisciplinary research in an innovative and collaborative environment. Application Process: Submit your CV, cover letter, and
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++ and CUDA) Code verification and validation of simulations Providing simulation results to project partners and customers Active participation in project, group and lab meetings, knowledge transfer
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models Experience with Pytorch, MONAI, CUDA or equivalent software libraries for developing deep learning models. Familiarity with medical image such as MRI, CT, or volumetric ultrasound. Knowledge
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Experience with Pytorch, MONAI, CUDA or equivalent software libraries for developing deep learning models. Familiarity with medical image such as MRI, CT, or volumetric ultrasound. Knowledge on common medical
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techniques. Preferred Qualifications: Knowledge of HPC matrix, tensor and graph algorithms. Knowledge of GPU CUDA and HIP programming Knowledge on distributed algorithms using MPI and other frameworks such as
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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, and deployment
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• Familiarity with operating HPC clusters (e.g., bash, Python) Preferred Qualifications • HPC programming skills (e.g., modern Fortran or C/C++) • Parallel programming skills (e.g., OpenMP, MPI, OPENACC, CUDA
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closure modeling and/or high performance computing environments (MPI, CUDA) • Expertise in software development and computing tools (C/C++, python, git, parallel computing, etc.) • Experience with deep
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computer science or related computational engineering disciplines. Experience with simulation frameworks for complex computer systems and architectures. Some knowledge of accelerator (CUDA, SYCL, HIP) and scientific
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct