78 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" PhD positions in Switzerland
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- University of Basel
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considered, please submit it by 15th November 2025. For further information, please contact Dr. Elena Jovanovska (elena.jovanovska@unibas.ch ). Where to apply Website https://academicpositions.com/ad
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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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(Bio-inspired) unsteady vortex formation and interaction More information about the lab and the ongoing and past projects can be found here: https://www.epfl.ch/labs/unfold/ ; Main duties and
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available for those wishing to learn Salary and Benefits: Gross living allowance: ca. CHF 6’144 per month Mobility allowance: ca. CHF 664 per month Family allowance: ca. CHF 617 per month (Values listed
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self-aware, autonomous scientific researcher. Free German courses available for those wishing to learn Salary and Benefits: Gross living allowance: ca. CHF 6’144 per month Mobility allowance: ca. CHF 664
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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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predict protein-protein complementarity, design artificial protein binders, investigate the effects of mutations on protein structure and function, and apply protein representation learning to uncover
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library. Strong interest in machine learning, reinforcement learning, and fluid dynamics. Ability to work independently and collaboratively in an interdisciplinary team. Excellent command of English, both
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qualifications include a Master's degree in computational biology or a related field. Prior experience with programming, statistics and biomedical research is essential, while experience with machine learning is
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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