54 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" positions at University of Basel
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practical applications, including solving mathematical reasoning problems. The ideal candidate has a strong background in machine learning and an interest in bridging rigorous theoretical insights with
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approaches Applying statistical modeling, causal inference, and machine learning approaches to identify determinants of developmental robustness Applying causal inference approaches to identify critical
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machine learning approaches Collaborating with experimental and clinical research partners Support and preparation of scientific reports and journal articles
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other means cannot be considered. For questions, contact Kathrin Eckerth by email: sek-mlps-englsem@unibas.ch with the subject Post-doc in English linguistics, Locher. Where to apply Website https
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Hospital, Copenhagen). The successful candidate will be responsible for designing and implementing the predictive modeling strategy of the project. This includes: Developing machine-learning prediction
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. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX
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information please see https://duw.unibas.ch/de/umweltgeowissenschaften/ or contact: Professor Christine Alewell, christine.alewell@unibas.ch . For information about application requirements and mandatory
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is 6th April 2026 23:59 CET. Preferred starting date is 1 June 2026. Applicants seeking further information please see https://duw.unibas.ch/de/umweltgeowissenschaften/ or contact: Professor Christine
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(oliver.heiri@unibas.ch ), for more information on the Geoecology group please visit https://duw.unibas.ch/en/research-groups/geoecology . We aim to start the project by 1 July 2026. Where to apply Website https
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applications for two PhD positions in the field of organic geochemistry and paleolimnology (https://duw.unibas.ch/en/research-groups/organic-geochemistry/ ). The students will be part of the SNSF-project ECO