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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | 2 months ago
programming, machine learning (scikit-learn, PyTorch/TensorFlow), ontologies (OWL/RDF), and/or computational cognitive modelling Interest in interdisciplinary research at the interface of computer science
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physiology is an asset Experience in statistics and data analysis of large data sets (including time series analyses and machine learning) Good programming skills Very good communication and interpersonal
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this with expertise in high-performance computing and artificial intelligence using unique scientific infrastructures. Are you excited about working at the interface of natural and computer sciences? At
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our group "Computer Vision and Machine Learning" in developing AI models and transferring them into production. In the master's thesis "Exploring latent spaces of deep networks for fault analysis in
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City Stuttgart Website https://www.f02.uni-stuttgart.de/en/ Street Pfaffenwaldring 7 Postal Code 70569 E-Mail bewerbung@f02.uni-stuttgart.de Phone +4971168560076 +49 6031 6709277 Fax +4971168550076
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-Scholl-Platz 1, D-80539 München no later than 10. May 2026 (date of receipt): https://www.efv.verwaltung.uni-muenchen.de/w1kikk (registration required).
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write this thesis. Interest in the field of battery development research. Very good written and spoken English; good written and spoken German desirable. Willingness to learn various electrochemical
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ScienceCountryGermanyCityRostockPostal Code18059StreetAlbert-Einstein-Straße 22Geofield Contact City Rostock Website https://www.uni-rostock.de/en/ Postal Code 18051 E-Mail alke.martens@uni-rostock.de STATUS: EXPIRED X (formerly Twitter
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mechanisms using computer simulations and the methods of non-equilibrium statistical physics. The Research The PhD student will work under the supervision of Dr. Philip Bittihn within the European Doctoral
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of the Faculty of History and the Arts, Prof. Dr. Julia Burkhardt, Ludwig-Maximilians-Universität München, Geschwister-Scholl-Platz 1, 80539 Munich,Germany, no later than 23.04.2026 (date of receipt): https