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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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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
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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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and publications. Profile A genuine passion for metabolomics and technology development with an impact mindset (turning ideas into usable capabilities). PhD in analytical chemistry, bioengineering
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, such as childcare or family responsibilities, or in combination with other projects or professional commitments. Profile We are looking for candidates with a PhD (or close to finishing their PhD) in
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respond to diverse mechanical cues from their environment, including adhesion, stiffness, tension, shear, pressure, and confinement. These cues are integrated across wide spatial and temporal scales, from
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PhD on top level in the field of architectural history and theory You bring founded experience in academic reserch and writing You bring appoved teaching experience from one or more academic