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DTU Tenure Track Assistant Professor in Nutrient-Focused Processing in Ultra-Processed Food Syste...
, bioactive compounds, and other key nutrients. Develop and apply machine learning and modeling techniques to analyse, predict, and optimize the effects of processing on food composition, food Ingredient
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machine learning models for the diagnosis of temporomandibular disorders (TMD) based on jaw motion time series data. Moreover, the successful candidate will be affiliated with the Comprehensive Center AI in
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of an identified area of the specification (Biology A level) Craft detailed explanations to questions to explain the logic and science in a way that actively contributes to learning and successful outcomes
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. Biomedical data science that combines methodology and implementation, in areas such as statistical modeling, natural language processing, bioimaging analytics, and machine learning/artificial intelligence
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candidate will be appointed to a full-time tenured position at the rank of Associate or Full Professor within the Faculty of Engineering. In addition to leading a world-class research program, they will teach
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Leveraging the spatio-temporal coherence of distributed fiber optic sensing data with Machine Learning methods on Riemannian manifolds Apply by sending an email directly to the supervisor
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Hub team as a Research Associate. The role involves designing and implementing robust machine learning pipelines, evaluating AI model performance, and advising healthcare companies on AI adoption
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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should have a graduate degree (Master 2 degree). Him/her scholar background should include: • statistical/machine learning, statistical inference, clustering, classification • deep learning, variational
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(History, Archeology, …). Expected skills: The candidate should have a graduate degree (Master 2 degree). Him/her scholar background should include: • statistical/machine learning, statistical inference