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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Infrastructure? No Offer Description Develop machine learning models to detect early signs of abrupt shift towards clean energy technologies and make climate action adaptive to this information. Job description
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Patient-derived organoids are the hallmark of personalized medicine with seemingly endless possibilities to match the right treatment to the right patient. As organoid data are often longitudinal in
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Develop machine learning models to detect early signs of abrupt shift towards clean energy technologies and make climate action adaptive to this information. Job description Positive tipping points
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where trustworthiness is essential. Today’s explainability methods often do not provide meaningful decision support and, in some cases, can even leak sensitive training data. Models are especially
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modeling, led by five team members. The current PhD position focuses on developing surveys and conducting statistical analysis of the unique microdata collected from households and firms across three
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Make a difference with your research. Join us to build advanced population models based on the field observations. You’ll collect and analyse data on conservation options - predator management
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PCM composites the RecyWax+ project combines multi-physics modelling approaches and physical experimentation of the thermal properties of the PCM composite. Throughout, theory is validated by synthesis
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critical role. The research will combine: Numerical modelling: develop and validate models to describe transport and separation mechanisms Experimental work: Design and operate and experimental setup using
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Job description Musculoskeletal disorders, affecting muscles, bones, joints, and associated tissues, are the leading cause of disability worldwide. Musculoskeletal models can be used for prevention
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unprecedented real-time visualisation of these processes, yet systematic investigation across diverse rock types and integration with predictive models remains lacking. In this PhD study, you will be performing