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Field
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data
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collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI
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application! Your work assignments Spatio-temporal processes are everywhere in science and engineering, with applications ranging from weather prediction to cardiovascular medicine. Developing machine learning
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knowledge of and/or experience with validation of prediction models (regression or supervised machine learning), health technology assessment, decision curve analysis, and/or value-of-information analysis
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will develop new methods for machine learning and dynamical systems, including generative modeling and system identification, with applications in biomedical modeling, large-scale autonomous systems
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contract is based on § 2 WissZeitVG. Your Tasks: Generative diffusion models (DMs) learn to reverse a diffusion process from an analytically known prior distribution to a target distribution that is inferred
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English. Preference will be given to those with (i) strong background in quantitative methods, geospatial methods, AI and machine learning; (ii) experience in high-performance and cloud computing; (iii
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bespoke methods – including advanced data modelling approaches (e.g., machine learning, digital twin models) and AI techniques where appropriate – to provide novel solutions that enable sports to make
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Helmholtz-Zentrum für Infektionsforschung GmbH | Braunschweig, Niedersachsen | Germany | 19 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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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical