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Lebensverläufe nach schwierigen Erlebnissen in Kindheit und Jugend» an. Interessierte Personen bitten wir, sich zur Vorbereitung mit diesem Projekt vertraut zu machen: https://www.nfp76.ch/de/ZYwwIq4IOWL9kQwd
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) at ETH Zurich invites applications for a tenured faculty position in the field of the Mathematical Foundations of AI for Science and Engineering (also known as Scientific Machine Learning). The new
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exclusively online to the following address : https://jobs.unige.ch/www/wd_portal.show_job?p_web_site_id=1&p_web_page_id=75852 by December 15, 2026 (23h59 Geneva local time). APPLICATIONS SENT BY E-MAIL
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to outstanding candidates from diverse scientific and medical backgrounds, including Biology, Medicine, Physics, Computer Science, and Engineering, who wish to pursue their research within one of our
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Information Modelling (BIM), Geographic Information Systems (GIS) or computer programming is a plus. A master's degree or professional experience in architecture is preferred but not required. The employment
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. Candidate profile Applicants should have a PhD in biomedical engineering, electrical engineering, computer science, data science, computational neuroscience, human movement science, psychophysiology
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, computer engineering, computer science, mathematical engineering, or similar. Proven track record in the Machine Learning, Artificial Intelligence, or Robotics, reflected through contributions to major
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candidates with A PhD in machine learning, computer science, applied mathematics, statistics, physics, engineering, or a closely related field, completed or near completion. Demonstrated expertise in
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research software engineering Support researchers in the practical use of scientific computing infrastructure and help translate research needs into robust technical solutions Contribute to the evaluation
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Essential MSc or PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field Exceptional BSc candidates with strong engineering experience will also be considered