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data, log-trace data from learning platforms, and panel data. Relevant areas of expertise include longitudinal data analysis, psychometrics, learning analytics, and machine learning. We are particularly
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accessibility by public transport or car (including free parking) 30 days of vacation Participation in the benefits program for employees („Corporate Benefits“) The BIO-MICRO project Please find a description of
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Fraunhofer IGD and the FBN team to safeguard an efficient collaboration and communication between behavioural biologists and computer scientists. The project is part of the KI-Tierwohl project (https://ki
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Helmholtz-Zentrum für Infektionsforschung GmbH | Braunschweig, Niedersachsen | Germany | 16 days ago
of German Experience in dynamic modelling of infectious diseases Laboratory methods for serology/ELISA (experience gained during MSc or BSc studies desirable) Knowledge on/ experience in Machine learning
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and simulation Prior experience with particle accelerators and/or FELs is highly desirable Familiarity with machine learning techniques is a plus but not necessary Excellent command of English is
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23.02.2026 Application deadline : 30.04.2026 The Autonomous Systems Lab at the University of Tübingen is searching for a Postdoctoral Researcher in machine learning (m/f/d, E13 TV-L, 100%) limited
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
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partners. The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course
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Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap-specific signals from raw