40 condition-monitoring-machine-learning Postdoctoral positions at Technical University of Munich
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premature deaths, especially among children, people with certain medical conditions and the elderly. With roughly 91% of the population living in urban areas and breathing polluted air, miniaturized detection
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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
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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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: - QUANTITATIVE VERIFICATION: analysis of probabilistic systems (Markov decision processes, stochastic games, chemical reaction networks), automata theory and temporal logic, machine learning in verification
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of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
learning • robotics and/or mechatronics • computer languages C, C++ and Python and interest to work in an interdisciplinary environment are desired. German language skills are necessary for this position
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of empirical research (quantitative or experimental) methods, • knowledge of statistics, programming languages (e.g., Python), natural language processing, machine learning is advantageous but not
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University Munich (www.tum.de). Accordingly, we are currently searching for PhD Students and Postdocs to join our team! PhD Students For PhD students, we are looking for persons that are willing to learn and
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, enrichment analyses - biological interpretation of data Your qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq
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of metrology for environmental applications, and monitoring greenhouse gas and pollutant emissions using atmospheric measurements and dispersion models. We are looking to grow our team from June 2022 onwards