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Excellent programming skills in PyTorch/JAX and experience working with GPUs and high-performance clusters. Strong mathematical skills with excellent understanding of statistics (e.g., hypothesis testing
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frameworks, e.g., Caffe, TensorFlow, PyTorch, and GPU-acceleration frameworks, e.g., CUDA will be a plus. Outstanding SW development and programming skills in C++, Python, ROS tools and libraries. Excellent
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will benefit from the Jean Zay supercomputer to perform intensive GPU calculations but also MARBEC/LIRMM GPU shared resources (https://umr-marbec.fr/recherche/dispositifs-de-recherche/den/ ). His/her
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, research fellows, scientists, software engineers, postdocs, and graduate students. Fellows will have access to the AI Lab GPU cluster (300 H100s). Ideal candidates will have a strong interest and proven
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that serves researchers and educators at the University of Utah and beyond. Responsibilities Kubernetes for AI/ML: Design and deploy highly available Kubernetes clusters, optimized for GPU utilization and AI/ML
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that serves researchers and educators at the University of Utah and beyond. Responsibilities Kubernetes for AI/ML: Design and deploy highly available Kubernetes clusters, optimized for GPU utilization and AI/ML
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Science Beamline (P61A/WINE), the lmaging Beamline (P05/IBL), and the Nanofocus Endstation of Micro? and Nanofocus X-ray Scattering Beamline (P03/MINAXS), along with supporting laboratories (https
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) Country United Kingdom Application Deadline 21 Jan 2026 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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40 h/ week Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Reference Number 101227453 Marie Curie Grant Agreement Number 101227453 Is the Job related to staff
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to clinical data; design interpretable representation spaces for tumor-immune dynamics and therapy response. Technical Expertise (25%) – Engineer LLM and diffusion/flow-matching pipelines; integrate multi-GPU