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Field
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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moments. All these factors are highly dynamic in the way they interact to impact racing tactics and trends. The specific objectives include: Historical analysis of racing from the past 3-5 years across
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their subsequent simultaneous analysis. This project aims at overcoming these challenges to reliably measure atmospheric levels of PFASs and model their respective emission strengths in Switzerland
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treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews
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, such as household decision-making, willingness to invest, adoption of renewable energy technologies, and social acceptance of innovations. The goal of the PhD is to develop validation methods, best
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analysis, focused on selected electrodes or brain regions. We would like to investigate how graph deep learning models can be designed to capture dynamics in brain signals for the accurate detection, and how
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Vacancies 2 PhD Positions to contribute to a project crafting the future of healthcare decision making Key takeaways In the section Health Technology and Services research at the University
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year. Working at the intersection of water engineering, environmental microbiology, robotics, and lifecycle analysis, you will evaluate autonomous underwater skimming robots that minimise energy use in
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regimes using simulation modeling Quantification of climate change impacts on protective forests (scenario analysis) Contributions to evidence-based management decision making in mountain forests
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. The system will leverage cutting-edge techniques in Natural Language Processing (NLP), Machine Learning (ML), and Multimodal Analysis to conduct adaptive interviews, assess candidate responses, and generate