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analytical techniques (HPLC, LC-MS, and GC), as well as computational tools. An integral part of the work will be the integration of biological data with medicinal chemistry principles to identify the most
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addressing the challenges of limited patient-specific data and uncertainty in model predictions. A key objective is to identify the appropriate balance between model complexity and clinical applicability
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through invasive catheter procedures. While these measurements provide valuable clinical information, they are costly, time-consuming and carry risks for patients. Developing reliable non-invasive
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, durability, and structural testing of cement-based materials is an advantage experience with data processing and analysis of material or structural response is desirable Personal qualities strong ability
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-scale testing, numerical modelling, and field investigations familiarity with strength, durability, and structural testing of cement-based materials is an advantage experience with data processing and
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, policy analysis) Interest in the social, ethical and political dimensions of digital health technologies, AI, and/or data-driven medicine Strong analytical and organisational skills to apply initiative
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technologies and ICT (e.g., blockchain, IoT, data analytics) in future energy systems. Willingness to contribute to academic dissemination (e.g., publications, conferences) and collaborative project tasks
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Sciences scientifically original and academically strong project proposal that is suitable for making an independent contribution to research within Information Systems strong analytical skills fluency in
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anthropogenic pressures. It will also provide spatially explicit information relevant to biodiversity conservation, ecosystem management and the preservation of culturally valued mountain landscapes. The PhD
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