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modelling is an advantage. Programming skills (e.g., C++, Python, CUDA) and familiarity with high-performance computing are considered assets. You are enthusiastic, self-motivated, and capable
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, evidenced by e.g. projects on Github. Familiarity with deep learning hardware / accelerators and GPU/CUDA kernels.
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programming preferred. Experience with C/C++, MatLab, Cuda, and/or IDL programming preferred. About the Department School of Physics and Astronomy: https://cse.umn.edu/physics Pay and Benefits Fixed Pay Rate
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systems (e.g. CUDA, OpenCL). Advanced Linux system administration skills, particularly for research computing environments. Experience with workload scheduling tools (Slurm, PBS, HTCondor) for efficient job
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the core computing languages necessary for machine learning and high-performance computing, including C++, Python and CUDA Knowledge of machine learning, high performance computing and data science Excellent
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Actions Home Help Job Description More Actions UC Davis Health Careers Sign In New User Previous Job Job Title Pharmacy Technician 2 (Cuda Eve) Next Job Apply for Job Job ID 81105 Location Sacramento Full
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/Fortran) Shared and distributed memory programming tools (e.g. OpenMP, MPI) Accelerator programming (e.g. CUDA, OpenCL, SYCL) Machine Learning libraries such as Tensorflow or PyTorch Serial and parallel
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or distributed computing Experience with GPU/CUDA, C and C++ programming Working knowledge of OpenCL, OpenACC, Python, MPI Preferred Qualifications PhD in Physics, Biophysics, Computer Science, Engineering
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 days ago
Galerkin spectral methods (CG and DG). Hands-on HPC programming (MPI, OpenMP, CUDA). Understanding of seismic workflows (modeling, FWI, RTM). This will be facilitated by collaborating with members of Makutu
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, OpenFOAM), and plasma physics (XGC, IPPL). Expected qualifications: A Master's degree in Computer Science or Applied Mathematics. Necessary knowledge: Modern C++, GPU computing with CUDA/SYCL, MPI, Krylov