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combines machine learning, legal applications, and empirical evaluation in collaboration with judicial partners. The project offers a unique opportunity to work on real-world, high-stakes AI systems in
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armasuisse Science and Technology and partners from industry and the Swiss Armed Forces. The research contributes to the scientific foundation of monitoring and rapid altering systems for underground
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of Environmental Engineering, ETH Zürich and matriculate in ETH Zürich. The research is related to development of experimental and modeling techniques to identify emission sources, simulate the airborne transport
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qualitative and quantitative analytical methods to model clinician attention, verbal reasoning, and documentation behaviour Develop and evaluate machine learning models, including unimodal, fusion, and
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tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/phd-position-computer-simulati… Requirements Research FieldEngineeringYears of Research Experience1 - 4 Research
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facilities in Switzerland, France, Germany, UK, Japan and the USA Data analysis and modeling will be done in collaboration with research groups that specialize in theoretical and numerical calculations Profile
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of cardiovascular anatomy and hemodynamics. The research will integrate modern machine learning with MR signal modeling, computational imaging, and fluidmechanis, with the ultimate goal of enabling faster, more