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, multi-modal data, and GPU-accelerated machine learning for materials science. Information We are seeking two highly motivated postdoctoral researchers to join the Horizon Europe project SIMU-LINGUA, a
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). Experience training AI models on GPUs. High motivation for research and a commitment to publishing at top conferences. Proven experience in submitting research to top-tier venues, such as ECCV, CVPR
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Agent records (using FreezerPro). Required expertise: State-of-the-art expertise in long-read sequencing technologies and associated bioinformatics pipelines, including proficiency with GPU-enabled Oxford
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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 16 days ago
of computing clusters and/or GPUs, as well as basic knowledge of computational fluid dynamics or numerical simulation, will also be valued. The ability to integrate computational tools with real clinical data
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development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D
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Integration of satellite observations, buoy measurements, and ship-based data into data-driven forecasting systems Demonstration of real-time forecasting workflows running on portable GPU-based edge computing
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. Experience with GPU-based training and high-performance computing. Interest in translating methodological contributions into high-impact medical AI venues (e.g., Nature Medicine, Nature Machine Intelligence
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direction is the generalization to parallel GPU computations. Task 4: Correctness evaluation of quantum communication systems and quantum protocols. This task will include approaches such as statistical model
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• Execute large-scale simulations on CPU and GPU-based HPC clusters • Analyze results, generate technical reports, and deliver project outcomes on schedule • Prepare scientific reports and publish in
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collaborative, international team. We offer Cutting-Edge Resources: Access to state-of-the-art compute and GPU infrastructure, including H100 and B300 GPU clusters. Innovation: The opportunity