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computational science, collaborating with leading European research groups and benefiting from advanced GPU and HPC infrastructure. Where to apply Website https://www.academictransfer.com/en/jobs/359110/postdoc-2
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Job Code 0005 Employee Class Civil Service Add to My Favorite Jobs Email this Job About the Job The successful applicant will assist in the adaptation of the PPMstar code to run well on GPU-accelerated
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, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized knowledge of Neural Rendering (NeRF/3DGS) or Satellite Photogrammetry. Demonstrated
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bioimaging and bioinformatics team at IBENS, under the supervision of Auguste Genovesio. The postdoctoral researcher will have access to a workstation as well as computing servers equipped with GPUs. Where
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specialists and set clear priorities to realize projects effectively and on time, building infrastructure that makes complex analyses faster and more efficient. Your team optimizes virtual computing power (GPUs
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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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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 9 days ago
deployment, · knowledge of GPU computing and large-scale training, · experience working in an HPC environment, · experience with data annotation pipelines or synthetic data generation. We offer: · work in a