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tools (e.g., Python programming) is an advantage. You enjoy working in an international team and have good communication skills. Proficiency in spoken and written English is required. For more information
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interdisciplinary collaborations such as the Collaborative Research Center 1371 “Microbial Signatures – Functional Relevance in the Digestive Tract” (https://www.sfb1371.tum.de/) and access to different core
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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experiences in working with remote sensing data, climate data and programming skills (R or Python) are desired. You enjoy working in an international team and you are keen on developing a key set of research
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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platform for early detection of cardio-metabolic diseases as well as characterization and classification of skin diseases. You will be part of our highly impactful research programs funded by European and
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these goals in different research frameworks and collaborative re-search with industry partners. Requirements Profile The following requirements apply for the position at the offer: • Excellent grade degree
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of novel components enhancing the thermodynamic cycle take a central role, focused on environmental awareness and reduction of fossil fuel consumption. The institute follows these goals in different research
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to develop a methodology for constructing 3D models Based on diverse details provided in the different kinds of 2D drawing views. Developing such a methodology requires the identification of drawing
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heterogeneity; namely non-iid and domain shift, e.g. multi-modal data acquired by different scanners and imaging protocols. Publish and present scientific results at international conferences and high-impact