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PhD programme with a focus on data science and research in the structure of matter. The graduate school covers data challenges from application fields such as structural biology, particle physics
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, inspection histories, operational performance data, hyperspectral imagery, train-borne video analytics and satellite soil-moisture products to build predictive models of vegetation-driven and water-driven
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that deliver healthier indoor environments, lower carbon emissions, and long-term building performance. By integrating Passive House and EnerPHit principles with real building data, the research will support the
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fairness in FairChoices: DCP Analytics Tool (www.fairchoices.org ) and integrate these with existing information on the cost-effectiveness of multiple health care interventions. To apply social welfare
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these with existing survey data. The PhD student will contribute to international journal publications, present results at conferences and seminars, and take part in research training and the academic life
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and uncertainty (e.g. demand evolution, renewable generation) influence system performance and trade-offs. The research will combine analytical modelling with data-driven and AI-based methods
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Are you interested in applying advanced data analytics and quantitative models to challenges in nutrition and health? This position at Fraunhofer-Chalmers Research Centre offers the opportunity
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The Brussels School of Governance, Department Institute for European Studies, Research Group European security in the Indo-Pacific age is looking for a PhD-student with a doctoral grant. The Centre
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PhD Position: Quantifying Indoor and Occupational Microplastic Exposure Faculty: Faculty of Veterinary Medicine Department: Department Population Health Sciences Hours per week: 36 to 40
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on the project choice/previous experience/interests, as a PhD student, you will gain hands-on experience in Synthetic chemistry and analytical techniques (HPLC, LC–MS, NMR) Designing and synthesising compounds