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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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: 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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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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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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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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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 1 month ago
promote equality and foster an open, inclusive work environment. Flüelastrasse 11, CH-7260 Davos Dorf Website Company-Video Where to apply Website https://academicpositions.com/ad/swiss-federal-institute
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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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Publications in top ML conferences and/or prominent journals in materials sciences and device physics Enjoy collaborating with other researchers in a friendly environment Be willing to supervise junior PhD and
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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
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strains Co-representation and reporting of BPL results in consortium meetings Co-coordination of tasks with all consortium partners Profile PhD in molecular biology, microbiology or industrial biotechnology