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-performance computing (HPC), parallel computing frameworks (such as MPI, OpenMP) and GPU acceleration. Proven experience administering, configuring, and optimising HPC clusters and GPU systems (e.g. CUDA
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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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computing (Rust, C, C++). Algorithm development for radio astronomy heterogeneous high-performance computing (CUDA, OpenCL) Basic Qualifications Bachelor's degree in EE or Physics. 5 years experience in
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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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the integration of both Convolutional Neural Networks (CNNs) and Spiking Neural Networks (SNNs). This position will involve training and optimizing these neural networks using Python frameworks, including CUDA
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., optimization, dynamical systems, graph theory, probabilistic modeling) or adjacent fields with engineering impact. (4) Fluency in prototyping and software development (e.g., Python, C++, CUDA, or ML frameworks
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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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. • Solid knowledge of numerical methods, including optimization, linear algebra, and geometry processing. • Experienced on GPU programming, familiar with cuda thread scheduling, allocation, and
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Microscaling Data Formats for Deep Learning INT4 Decoding GQA CUDA Optimizations for LLM Inference Pruning and Distillation to Enable Llama 3.2 1B and 3B Models Suitable for Mobile Devices PyTorch Distributed