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1 Apr 2026 Job Information Organisation/Company La Rochelle Université Research Field Computer science Environmental science Computer science » Modelling tools Computer science » Programming
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frameworks (e.g., PyTorch). Familiarity with GPU-accelerated environments, virtualization tools, and prototyping using real testbeds (e.g., SDR). We expect a diploma in computer science or telecommunication
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community. We provide the resources to match your ambition: Industrial-Scale Computing: Exclusive access to massive GPU clusters and high-performance computing. Guaranteed Talent Pipeline: Generous
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for Computer Graphics and Real-Time Rendering. By using ANNs, coded for high-performance on cross-vendor GPUs, we aim to create new techniques for global illumination and material models. The subject works with
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models on GPU infrastructure (SSH access) and distributed computing environments. Strong problem-solving, documentation, and communication skills across technical and non-technical contexts. Ability
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biology. Please include a cover letter with your application detailing your qualifications and experience for this position. Describe a deep learning project you have executed. Projects in computer vision
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your bottom line. Total Compensation Calculator: http://www.cu.edu/node/153125 Equal Employment Opportunity Statement: CU is an Equal Opportunity Employer and complies with all applicable federal, state
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or TensorFlow. Practical background in training and validating models on GPU-based and distributed computing environments. Working knowledge of containerization tools and orchestration platforms (e.g. Docker
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NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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offers and actions on https://cluster-ia-enact.ai/ . You will work in a rare environment at the intersection of frugal AI, analog computing, reconfigurable electronics and THz imaging. The PhD is directly