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. Where to apply E-mail lorraine.dubuis@unige.ch Requirements Research FieldPsychological sciencesEducation LevelPhD or equivalent Skills/Qualifications Desired profile: PhD in psychology, neuroscience
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methodologically strong and motivated to work at the intersection of applied machine learning, social sciences, and natural sciences. Essential qualifications: A completed PhD in data science, computer
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depth. PhD degree in Physics, optical engineering, biomedical engineering, electrical engineering, or closely related fields Excellent skills in development of complex optical systems Experience in
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: Experience with analyzing GPS tracks Good data-handling skills and ability to use R (compulsary) and preferably also Python and/or GIS competently Statistical/causal inference knowledge PhD degree in a related
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evaluation. Collaborating with heritage partners (e.g., Swiss National Museum, SIK-ISEA) and preparing evaluation reports and a white paper for applied use. PhD in Digital Humanities, Imaging Science, Computer
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with the successful candidate, depending on their background and interests. Profile • PhD in Mathematics (to be completed by the start of the position) • Strong research record in stochastic analysis
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 1 month ago
(RuzicaDadic), University of Fribourg (Martina Barandun and Horst Machguth), and ETHZurich (Evan Miles). The core team consists of the 4 PIs, 4 PhD students, and 4 Postdocsand aims to quantify the impact of
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, coverage), publish at top-tier AI/ML venues, and contribute high-quality research code. Application deadline: 30th January 2026 Where to apply Website https://careers.werecruit.io/fr/idiap/offres
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Zurich, PSI, and international partners More information about the project and the group can be found on our website . Starting date: flexible in 2026 Employment: full-time Profile PhD in physics or a
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involve teamwork, including coordination with PhD students and other postdoctoral researchers. It is important to demonstrate the spirit of collaboration without compromising research independence. Your