223 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" Postdoctoral positions in Germany
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. If you do not yet have a transcript evaluation, please note that you may have to request one if your application is successful. For further information, please visit the website: https://www.kmk.org/zab
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include the University of Oxford, Imperial College London and Ukrainian and British policymakers. What we look for PhD in a policy-related field (e.g., public policy, political economy, economics, political
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projects within the Clusters of Excellence ‘Machine Learning for Science’ and ‘Image-Guided and Functionally Instructed Tumor Therapies (iFIT)’. Requirements PhD in Bioinformatics, Computational Biology, or
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-Phenomenology (hep-ph) , High Energy Physics , High Energy Theory , Machine Learning , Neutrino physics , Particle , Particle Physics , Particle Theory , QCD , Theoretical high energy physics , Theoretical High
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: analysis of probabilistic systems (Markov decision processes, stochastic games, chemical reaction networks), automata theory and temporal logic, machine learning in verification, building model checkers
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: https://www.pisa.tum.de/pisa/jobs/ Für eine der PISA Hauptdomänen (Lesen, Mathematik, Naturwissenschaften) nach Wahl wird zum nächstmöglichen Zeitpunkt ein*e Postdoc gesucht. Nähere Informationen zur
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is expected. Background Information: Nat. Chem. 2015, 7, 105; Chem. Eur. J. 2019, 25, 4590; Angew. Chem. Int. Ed. 2019, 58, 418; Nanoscale 2021, 13, 19884. www.sengegroup.eu https://www.ias.tum.de
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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machine learning algorithms Strong communication skills and ability to work in interdisciplinary teams Fluency in spoken and written English We offer: A dynamic and interactive research environment as
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
for outstanding candidates, with a successful degree (master/ diploma/doctoral/PhD) with exceptional records. A strong disciplinary background in • control, system theory and optimization • machine learning