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with the Swiss National Science Foundation regulations for doctoral candidates (https://www.snf.ch/media/en/yXApuFw4ml0TPYe2/Annex_XII_Ausfuehrungsregl… ) for the time of their PhD (36 + 12 months
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Your position A fully funded PhD position is available in the Computational Pharmacy group at the University of Basel. The successful candidate will contribute to ongoing research on the development
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strong support for personal and professional development. The PhD students will be enrolled in the ETH Zürich doctoral program. The position is available from April 1st 2026 or upon agreement. We live a
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crucial insights. In this project, you will contribute to the development of AI-driven methodologies for experimental fluid mechanics , focusing on: Designing multi-fidelity neural networks for adaptive
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and flow field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision
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is the development ferroelectric lead free ceramics sintered below 500°C and the analysis of their mechanical and electromechanical properties of elastomers with piezoelectric properties using 3D
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Strong command of R Didactic competence and enthusiasm for teaching Willingness to collaborate with colleagues, and to contribute to the academic activities and further development of the Political Science
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of adaptive radiation and associated key innovations in the evolution of freshwater diatoms. By integrating morphology, physiology, genomics, transcriptomics, and computational modeling, we aim to (i) determine
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performed in a holistic multidisciplinary approach in close collaboration with partners from UHA, France. The foreseen results of the project shall contribute to the development of optimized textiles used
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probe microscopy. Our research focuses on using single electron spins in diamond as sensors to explore magnetic phenomena at the nanoscale. This doctoral project will center around the development and