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discovery Single-cell multiome data analysis at ultra-large scale (>100 000 cells per donor) Spatial transcriptomics Clonal evolution and phylogeny Copy-number changes and complex rearrangements and their
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or interdisciplinary field Strong skills in quantitative methods, ideally with experience in surveys, survey experiments and causal inference techniques. Knowledge of text-as-data methods or machine
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disciplines with PhD Extensive knowledge of machine learning/artificial intelligence and big data science Extensive knowledge of programming languages (ideally Python) Basic knowledge of synchrotron research
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to build a collaborative scientific carrier in computer science and medical data analysis at a German top-ranked university. Help to acquire, mentor and teach students (e.g., PhD, MSc, BSc, seminar series
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research, teaching and knowledge transfer to society on artificial intelligence, machine learning, data-centered engineering and related data and knowledge-based technologies, with special dedication
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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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statistical topic modelling Experience with natural language processing Experience with statistical methods and machine learning Ability to extract and process large numbers of documents from the internet
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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