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, and contributing to grant applications. The post offers opportunities to work with international research groups and contribute to open-source bioinformatics tools. Experience with deep learning
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 2 months ago
with expertise in medical image processing—particularly registration and segmentation—and proven experience in deep learning, with a focus on ultrasound imaging. Prostate cancer diagnosis relies
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networks, financial networks, temporal and dynamic graphs, uncertain graphs, explainability and fairness of deep learning methods on networks. The aim will be publishing several research papers at top-tier
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methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
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National Aeronautics and Space Administration (NASA) | Cleveland, Ohio | United States | about 2 hours ago
designed to advance NASA’s missions in space science, Earth science, aeronautics, space operations, exploration systems, and astrobiology. Description: Exploration to deep space will require unprecedented
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(or near completion) in computer science, machine learning, statistics/biostatistics, computational biology, data science, physics, or a related field. Experience with modern deep learningframeworks (e.g
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the world’s largest supercomputers (Polaris, Aurora) and some of the most advanced characterization tools in the world at Argonne and Sandia National Labs. Candidates with a background in deep learning
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Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular
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multimodal deep learning models that integrate imaging and clinical data to personalize treatment and follow-up strategies. In the Netherlands, around 75% of patients with an abdominal aortic aneurysm (AAA