40 experiment-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in Switzerland
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, building technology, material science or a related discipline. Candidates without a PhD but with equivalent research experience and expertise may also be considered for an alternative appointment as a
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. Prior experience with animal models, 3D culture systems and/or computational analyses will be an advantage. The salary will be according to EPFL standards. Informations Formal applications should be
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from candidates with: A PhD in anthropology or a closely related discipline (completed before the start date). Strong qualitative research experience. Regional expertise relevant to one of the two
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different disciplines. Experience in electrochemistry, solid-state chemistry, neutron or synchrotron techniques, spectroscopy, or related methods will be considered an advantage. The successful candidate is
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virtual reality as an experimental platform, prior VR experience is not necessarily required. We are particularly interested in candidates with strong expertise in experimental systems, physiological
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to advance the state of the art in generative AI. Prior experience with biological or biomedical data is not required. The position comes with dedicated access to the Swiss National Supercomputing Centre and
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part of a collaborative team to plan and execute experiments Maintain knowledge of published developments in research field and recommend alternative strategies Plan and organize workload to meet project
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science, chemistry, or related fields, with a strong publication record. Prior experience in flow-cell electrochemistry, in-situ spectroscopy (UV-Vis, Raman, FTIR), or 3D printing and polymer processing is
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familiar with contemporary construction techniques and have an interest in 20th-century construction techniques or vernacular architecture. Experience in Life Cycle Assessment (LCA), Building Information
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Experience with machine learning and/or statistical modeling applied to biological data Proven expertise in single-cell data analysis (scRNA-seq and/or scATAC-seq) Interest or experience in multi-modal data