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order to expedite the simulation, MagTense is based on a core implemented in the Fortran programming language, and it relies on the platform CUDA for parallelization of the computation over several GPUs
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communications. Preferred Knowledge, Skills, and Abilities: You have experience developing and applying machine learning models You have experience in ab initio molecular dynamics. You are familiar with CUDA
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maintaining computational tools for biological data analysis. Proficiency in programming, experience with high-performance computing and GPU acceleration tools (e.g. CUDA), and deep learning frameworks such as
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, along with any other relevant applicant material. Strong preference for C, C++, CUDA experience. Salary: $70,000 The salary of the finalist selected for this role will be set based on a variety of factors
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++/Python/CUDA programming for deep learning. Demonstrated development of new deep learning methods for MRI. Experience in MRI image reconstruction; motion and distortion correction in MRI. Track record
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written in Python based on the NumPy, SciPy, CuPy, and mpi4py modules. It makes use of optimized BLAS, LAPACK, and FFT libraries for both CPU and GPU architectures. Through CuPy, custom GPU (CUDA/HIP
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programming skills and concepts Experience with fundamental OS and storage concepts. Experience with programming heterogenous architecture. Preferred Qualifications: Experience with CUDA programming; Experience
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, CPS, MILC, QUDA, Grid, etc.) is highly desirable. Familiarity with C/C++ and accelerator application programming models such as CUDA, HIP, SYCL, OpenMP, Kokkos or Raja, vectorization; MPI; and one-sided
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
Experience Candidates are expected to have strong publication record in biomolecular modeling and computational biophysics/chemistry. Programming skills (e.g., bash scripting, python, Fortran, C++ and CUDA