20 data-"https:"-"https:"-"https:"-"https:"-"Conservatorio-di-Musica-A" PhD positions in Switzerland
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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of Zurich and Wageningen University & Research. The four-year STEPS project focusses on developing data-driven and machine learning methods to monitor CO2 and NOx emissions using the upcoming satellite
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. Please submit these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/phd-position-in-data-driven
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analyze how these factors influence vote choice, and how the role of quality in elections can be strengthened. Empirically, the project combines surveys, survey experiments, and text-as-data methods.
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development of electrochemical sensors detecting environmental pollutants, providing real-time information for effective management. Past and current work includes electrochemical sensors for airborne virus
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-based optimization, enabling autonomous measurement campaigns and real-time data assimilation. This research combines fluid mechanics, artificial intelligence, and robotics to establish the foundation
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have since helped halve global mortality, but this progress is threatened by rising insecticide resistance. We build quantitative, data-driven models to forecast the spread and impact of resistance
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Computing, University of Basel), and 14 clinical partners across Switzerland. The project aims to advance the Family Gene Toolkit (FGT) v2.0, a digital platform that offers reliable information and prepares
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interdisciplinary team including computer scientists, experimentalists and clinicians. ■ You will be involved in cross-disciplinary collaborations and have training opportunities to further develop and grow your
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, the candidate should be committed to: doing field work, wet-lab work, learning about bioinformatics, including R and shell programing, and analyzing data using population genetics tools and theories