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Field
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with in-depth knowledge of parallel programming (GPU, multi-threading, etc.). - Familiarity with standard collaborative development tools: Git, GitHub, CMake, Guix-HPC, Spack, GTest, CTest, etc
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simulation methods, GPU-accelerated computations, several programming languages, and presenting results to wide technical and non-technical audiences. Additionally, the candidate will also develop theory and
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Researcher (R2) Application Deadline 18 Apr 2026 - 21:59 (UTC) Country Switzerland Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a
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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
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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streams while developing an independent research program aligned with Center priorities. This role includes managing experimental design and execution, contributing to high-impact publications, mentoring
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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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with OFDM modulation required. Skills Programming skills in MATLAB and or Python required, experience with wireless testbeds desirable, some familiarity with GPU programming desirable (to support
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Master’s theses Requirements: Master’s or PhD degree with above-average results in Applied Maths (analysis, numerics, modeling) or in a comparable program with a strong math. focus and knowledge in
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in top-tier machine learning/AI conferences and/or leading scientific journals. Excellent programming skills and hands-on experience with leading machine learning frameworks (e.g., TensorFlow, PyTorch