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equivalent degree in physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers to help you balance work and family life Further training opportunities
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at the workplace, from compute and GPU servers to supercomputers Opportunity for a PhD (Dr. rer. nat.) in one of the group’s diverse research areas Salary according to the public service pay scale (TV-L E13
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researcher with a proven track record in areas relevant to auto-tuning, focusing on ML-driven compiler optimization, transfer learning, and programming for heterogeneous systems across CPUs, GPUs, and
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researcher with a proven track record in areas relevant to auto-tuning, focusing on ML-driven compiler optimization, transfer learning, and programming for heterogeneous systems across CPUs, GPUs, and
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Good knowledge of AI and applied Machine Learning Hands-on experience with High Performance Computing Systems Basic knowledge of System Architecture of Supercomputers and NVidia-GPUs Practical experience
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, parallel/distributed computing, as well as diverse architectures and understanding of its impact on application performance Knowledge in GPU-based programming and modelling of scientific simulations
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computers Desirable: Knowledge in standard HPC programming (C/C++, Fortran, MPI, OpenMP, GPU programming, etc.) Experience supporting application developers German language is an advantage You don’t need
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, this position will primarily focus on optimising GPU utilisation for AI and molecular dynamics applications. About your role: Work closely with our industry partners on a high-performance computing (HPC) project
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performance on neuromorphic hardware. What you will do Develop and train CNN and SNN models using frameworks like Keras, PyTorch, and SNNtorch Implement GPU acceleration using CUDA for efficient training