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, engineering, physical science or related technical discipline. Experience: Expertise in developing and training AI models Proficiency in Python Experience with HPC (GPUs preferred) Related Skills and Other
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provides high-performance GPU computing resources that support the design and training of advanced AI models. The research agenda of CVI2 focuses on cutting-edge topics such as 3D understanding and
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platforms and our local CPU and GPU clusters; implementing Python tools for automating CSP/DFT calculations; - Participation in the scientific activities of the Applied Quantum Chemistry group (IC2MP) and the
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computing software libraries (e.g., Trilinos, MFEM, PETSc, MOOSE). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance
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computing environments, and GPU programming. Necessary skills include knowledge of data processing using software (e.g., Matlab, R, IDL) and/or statistical/mathematical programming languages (e.g., R, Matlab
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | 29 days ago
Behavior (CASCB), providing access to shared infrastructure, high-speed data networks, and central technical services. Computational needs will be met through multiple layers of resources: local GPU-equipped
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advanced compilation techniques for scientific and AI applications on heterogeneous GPU clusters. Research topics include scheduling, memory management, communication–computation overlap, and performance
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environments. Experience with parallel computing environments, HPC in a Linux environment. Experience with surrogate modeling. Experience with data analytics techniques. Familiarity with C++ and GPU programming
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100% funding per SNSF guidelines (~CHF 90'000/year) Access to modern GPU clusters and confidential-computing infrastructure Collaboration with leading researchers in AI & HPC systems and digital health
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and GPU-accelerated tools for circuit and system design optimization, addressing challenges in physical design, timing analysis, and large-scale hardware design automation. The researcher will