24 machine-"https:" "https:" "https:" "https:" "https:" "https:" "https:" uni jobs in Switzerland
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through innovative biomedical research and engineering solutions, translating basic science into medical knowledge and healthcare innovations. The Pediatric Disease Modeling Lab (https://dbe.unibas.ch/en
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(https://dbe.unibas.ch/en/research/data-driven-modelling-analysis/pediatric-disease-modeling-lab/) is seeking a Data and Computing Technician to build and maintain the data and computing backbone of a
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référence. Les candidatures sont à déposer au format PDF via la plateforme de recrutement de l’Idiap : https://careers.werecruit.io/fr/idiap . Délai de postulation : 12 octobre 2026 Role Summary As Deputy
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innovations. The Pediatric Disease Modeling Lab (https://dbe.unibas.ch/en/research/data-driven-modelling-analysis/pediatric-disease-modeling-lab/) is seeking a Senior Scientist to help lead a growing research
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innovations. The Pediatric Disease Modeling Lab (https://dbe.unibas.ch/en/research/data-driven-modelling-analysis/pediatric-disease-modeling-lab/) is seeking a Data and Computing Technician to build and
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sustainable and climate-neutral university . You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive
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and Communication Sciences, are strongly encouraged. The candidate's ability to teach STEM subjects and/or bioengineering topics will be a key selection criterion. EPFL offers world-class research
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the position of: Lecturer for the Module M05 'Computer Vision & Perception' 10 ECTS (18%) Start date: August 1st, 2027 Module completion: each autumn semester (beginning of August to end of January) Description
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the field of the Mathematical Foundations of AI for Science and Engineering (also known as Scientific Machine Learning). The new professor will lead an internationally high-profile research and teaching
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of computational and applied mathematics, including but not limited to data-driven numerical modeling, scientific machine learning and AI for science and engineering, computational uncertainty quantification