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and domains. Ability to troubleshoot connectivity issues and familiarity with vulnerability management and patching processes. Python and nVidia CUDA modules setup and configuration. Relational database
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CUDA and scientific computing libraries (e.g., NumPy, SciPy). Workload: Approximately 15 hours per week on average during the semester, with the possibility of increased working hours (up to 40 hours
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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
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Slurm) and package managers (Spack or similar); and 12. Technologies for heterogeneous large-scale computing (CUDA-aware MPI). This position is eligible for LBNL's Employee Referral Program benefit(s
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. Experience with MatLab, CUDA and IDL programming preferred. About the Department School of Physics and Astronomy: https://cse.umn.edu/physics Pay and Benefits Pay Range: $15.25 - $20 per hour; depending
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, CUDA. B3 Knowledge of UK data protection laws and certification and accreditation schemes related to the processing of sensitive data for research. Skills Essential: C1 Excellent strategic leadership
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Computing (HPC) knowledge around cluster builds, software, parallel computing, workload management, and cluster management. Knowledge with CUDA Programming Workflows, GPU programming, and GPU support
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using GPU/CUDA clusters for AI/ML and/or image processing. Proven ability to work in a dynamic environment and support large data systems. Effective documentation skills, including ability to prepare
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Pytorch, CUDA, Docker, vllm, TGI 6. Familiarity with platforms AWS, GCP, Azure, GitHub, HuggingFace, Spark/Airflow 7. Familiarity with Large Language Models and/or NLP will be advantageous 8
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needs as well as the ability to work in teams Desirable qualifications Knowledge of German Special knowledge in one of these areas is a plus: HPC (e.g., Workload Scheduler, CUDA, Infiniband) Storage (e.g