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languages; experience with GPU programming (e.g., CUDA) is highly desirable. Background in optimization, image-guided radiotherapy, medical imaging, or computational modeling. Experience with treatment
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learning architectures for scientific or high-performance computing applications. Background in software performance evaluation, profiling, and optimization on CPUs and GPUs. Knowledge of common numerical
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disease insights. The lab has state-of-the-art computing capabilities with an in-house cluster serving 80 CPU cores and 1.5TB of RAM, as well as a newly acquired NVIDIA DGX box with eight H100 GPUs and 224
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variety of computational devices (e.g. CPUs and GPUs) while ensuring overall consistency and performance. - contribute to identify new CSE applications domains, such as condensed matter systems, quantum
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techniques such as yeast display and deep mutational scanning, or computational candidates with experience in generative AI, reinforcement learning, or agentic AI. The lab is supported by world-class
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experimental data and workflows. The team drives innovation in algorithm design, GPU-accelerated computing, and quantum-ready methodologies applicable to complex scientific problems across the experimental
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data from the European XFEL facility at DESY. Project website: https://www.mpinat.mpg.de/628848/SM-Ultrafast-XRay-Diffraction Your profile Eligible candidates have strong skills in computational physics
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to develop and translate advanced computational tools that directly impact patient care in a clinical environment. Responsibilities: Develop GPU-accelerated dose calculation and optimization algorithms
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2027 - 03:31 (UTC) Country Luxembourg Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing