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University Duties This PhD project is part of the AFLOW consortium supported by the Swedish Energy Agency and focuses on multi-scale modelling of aqueous organic redox flow batteries, to build a predictive
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the fields of fairway design, intelligent waterway engineering and autonomous shipping, handling of new fuels on ships and in ports, and AI-based predictive analytics for ensuring maritime safety. Enhancing
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-physical properties of insulating biobased concretes in order to provide the input parameters for modelling. Multiphysics predictive modeling: to reduce the cost of experimental tests and provide a decision
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Researcher to join an interdisciplinary project focused on improving early diagnosis and risk prediction in adolescents with early-onset psychosis, with particular emphasis on schizophrenia and bipolar
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of complex epidemiological and genetic data, in computational and population health sciences and in disease risk-modelling and risk-prediction. Eligibility criteria The project will suit students with strong
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currently lack reliable uncertainty estimates, limiting error detection and automation. The UMLFF project aims to develop next-generation MLFFs with built-in uncertainty predictions to enable safe, automated
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network performance data obtained from user devices. Assist in the development of basic models to predict or explain network behaviour under different conditions. Contribute to the improvement of internal
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Offer Description Mission: Collaborate in the development of strategies for predicting and monitoring railway-induced vibrations. Functions to be developed: Develop prediction models for vibrations
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outputs and insights, you will further extent the research to prediction models and different product development, which can be tested on pilot scale as well. Duties As a Ph.D. student you are expected
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Silva. Grant duration: Initial duration of 36 months, with the predicted starting date in April 2026, on an exclusive basis eventually renewable but never exceeding the project duration