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Field
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. Required qualifications include a PhD or equivalent degree with exceptional expertise in machine learning as well as postdoctoral qualifications and teaching experience equivalent to the requirements of a
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, including gas turbines and combustion engines. We combine advanced computational fluid dynamics, theory, machine learning, high-performance computing, and experimental methods to investigate and model complex
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, pathology and outcome data Multi-agent and predictive AI development: Develop machine-learning components for patient-trajectory modelling, recurrence and survival prediction, and integrate them
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for Philosophy of Machine Learning for Science (m/w/d) to commence as soon as possible. The tenure-track position is embedded in the Cluster of Excellence “Machine Learning: New Perspectives for Science
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08.06.2026 Application deadline : 15.07.2026 The Cluster of Excellence "Machine Learning - New Perspectives for Science" at the University of Tübingen offers several positions as Early Career
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PhD and/or postdoctoral record with outstanding scientific achievements, international research experience, and publications in relevant journals and/or in top-tier machine learning venues (e.g
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” at the Faculty of Humanities. The position is located at an office at the management of the DLA and develops the field of exploring and analyzing analogue archive collections with the help of machine learning
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team explores new applications of AI in collaboration with the diverse scientific disciplines associated with the Helmholtz Association. Within our lab “Applied Machine Learning”, you will play a crucial
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, motion tracking, and computer vision methods, we study both typical development (with a strong focus on adolescence) and atypical social behaviours in clinical populations to improve the understanding and
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Personalization and adaptive reasoning systems AI for Education Doctoral students will also have access to specialized courses in: Artificial Intelligence, Machine Learning, and Edge Computing Advanced