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clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology. The programme focuses on adrenal disorders as a case study for advancing digital
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monitoring allow personalised diagnosis and treatment. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into
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of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology. The programme focuses on adrenal
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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cloud data centres. However, this can come at the cost of performance and slower function processing, which manifests as higher energy consumption and increased operational costs (OpEx) for operators. So
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adrenal insufficiency using real-world, continuous data streams. The rationale is to investigate how cortisol levels influence tissue glucose, blood pressure and sleep (sleep radar) and how it correlates
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and partner urban sites, the successful candidate will collect and analyse real-world environmental data to evaluate how vegetation interacts with the built environment. You will be supported by a
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in Work Package 1 of the ENDOTRAIN network and aims to investigate how endocrine rhythms are affected in patients with primary adrenal insufficiency using real-world, continuous data streams
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and spatial resolution of regional ocean model data around Europe, having broad use cases in mind such as offshore energy and aquaculture. As global climate variability intensifies, precise regional
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15th February 2026 Languages English English English PhD Research Fellow in Multimodal Large Language Models for Patient-Generated Data in Shared Decision Making (DC7) (ENDOTRAIN) PhD position