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professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/ Your work assignments Machine learning, and in particular deep learning, requires
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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the
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the development of computational pipelines and reproducible workflows for the analysis of biological and biomedical data using deep learning techniques; • promotion of technology transfer and support
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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
intervention.Insights from these engagements will be integrated with outputs from advanced AI models (e.g.,geospatial deep learning, graph neural networks, and explainable AI ) to refine the AMR risk maps and
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Responsibilities: Develop and apply machine learning and deep learning models (e.g., graph neural networks, generative models, transfer learning) for materials property prediction, interpretation, and
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Infrastructure? No Offer Description Are you passionate about combining the directed evolution of diverse biomolecules with deep learning approaches and contributing to the development of better (bio
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FAU DCN-AvH. Chair for Dynamics, Control, Machine Learning and Numerics | Erlangen, Bayern | Germany | 4 days ago
Zuazua , invites applications for a postdoctoral researcher position in applied mathematics within the ERC Advanced Grant CoDeFeL – Control for Deep and Federated Learning. Position Details
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background in machine learning, deep learning, artificial intelligence, or computer vision Strong Python programming skills Experience with at least one deep-learning framework, preferably PyTorch An
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Heinrich Heine University Düsseldorf | Düsseldorf, Nordrhein-Westfalen | Germany | about 7 hours ago
leading expert on the development of a human brain atlas at microscopical scale. She has applied deep learning, image analysis and advanced computing to develop the Julich Brain atlas and BigBrain, which
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following: life cycle assessment, life-cycle cost analysis, pavement simulation, machine learning, deep reinforcement learning, and/or physics-informed modeling frameworks; and demonstrated ability to