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learning, computational mathematics, and probabilistic modeling, with direct applications in medical imaging and beyond. Details can be found in the link below. The position is suitable for disabled persons
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fine-tune machine learning and deep learning models to extract meaningful patterns and predict metastatic behavior Collaborate closely with experimentalists for mechanistic dissection of multimodal
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/d) in Energy Informatics, specifically for a DFG project in wind power forecasting using machine learning. You are passionate about applying cutting-edge information technology to solve the energy and
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applications. Our overarching aim is to obtain a holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms
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The »High-Performance Cutting « department develops technologies and application-oriented solutions for machining along the entire process chain - from process design and process simulation to real
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Organoid Engineering for Multi-Organ Interaction Studies (POEM) program ( www.uni-heidelberg.de/en/cctp-poem ) brings together expertise in material science, computer science/machine learning, biophysics
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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are in engineering sciences, mathematics, computer sciences, natural sciences and medicine. Our economics, social sciences and humanities are indispensable and crucial disciplines in a modern university
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architecture exploration, hardware/software co-design and operating/runtime systems. Typical application domains are e.g. signal-/image processing, artificial intelligence and machine learning. Tasks: research