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eventually design genes and cells for biotechnological applications. Our research group will develop new AI modeling paradigms to learn from such multi-modal and multi-species data effectively. This will allow
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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
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strong motivation to learn and push the boundaries of our current knowledge further is required. Ability to work in a team is essential. We are looking for an individual with a high willingness to take
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mentality for cutting-edge research in various fields including robotics, machine learning and systems intelligence. An exceptional opportunity to experience research in a highly inspiring international
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, Brain Machine Interfaces, Computational Neuroscience Desired qualifications: Biomedical laboratory experience Experimental design Sensor fusion Machine learning Control system development Biomedical
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. • Exploring machine learning architectures (convolutional neural networks, long short-term memory networks etc.). • Building physical/mathematical models including aspects of image formation in tomography
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offer • A stimulating, high-paced environment for cutting-edge research in various fields, including robotics, machine learning, and systems intelligence • An exceptional opportunity for high-end research
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networks to transfer essentially part or all of resource-intense planning, learning, and control computation to the edge and beyond. This transfer will allow the robots to be significantly lighter, more
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, continued education, life-long learning and provide excellent opportunities for professional growth. Situated on the foothills of the Alps, Munich is consistently ranked as one of the most vibrant and
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the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We