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analytics. This PhD project focuses on methods development to support pharmacovigilance using real-world data (RWD). You will define, implement, benchmark, and validate workflows for reliable detection and
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structure shape below-ground microclimates, which in turn regulate soil microbial processes and influence ecosystem carbon cycling across. About the position Climate change is increasing the frequency and
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Car tires are very important and complex parts with high safety and reliability requirements, responsible for maintaining the contact between a vehicle and the road. Tires are subject to wear due to
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observations, semi-structured interviews, controlled language tasks, as well as advanced statistics (network analysis). Together, the studies you will conduct will inform us about when and how brokering has
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of methods, including semi-structured interviews, diary-based methods (Experience Sampling Method), scenario-based judgement tasks, attitude scales, and parent-child joint problem-solving and narrative
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are being made with incomplete information. Synthetic data offers a way out: realistic-but-artificial datasets that preserve the statistical, temporal and physical structure of real energy data without
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for your systematic, structured, and accurate approach, driven by strong perseverance. You are confident in asking critical questions to further your research and you identify opportunities, effectively
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and a good command of academic English; Excellent research and analytical skills; Experience in computational linguistics and/or affinity with the framework of Construction Grammar is a plus. Terms and
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other markets, driving further innovation in healthcare and related technologies. The goal of this project is to find a reliable packaging technique for silicon chips with embedded microfluidic channels
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of ecosystem services. Your duties and responsibilities include: Develop a Research Proposal and a Training and Supervision Plan, to structure the PhD trajectory Advancing conceptual thinking by linking farm