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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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documents: CV with list of publications A one page summary of your PhD (up to 3,500 characters) A two page presentation of your research plans during your time in the professorship (up to 7,000 characters
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, you will be encouraged to develop independent ideas, propose new concepts, and test them experimentally and/or computationally. The role is ideally suited to strengthen your pre-existing expertise and
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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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connectivity Profile PhD in neuroscience, biology, bioengineering, or a related field Strong background in cell culture, including primary neurons or iPSC-derived cells Experience with electrophysiology (e.g
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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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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
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the innovation project. Within the framework of an innovation project with well-defined objectives, you will be encouraged to develop independent ideas, propose new concepts, and test them experimentally. The role