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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation
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annotation, and emerging machine-learning and generative methods for spectra or structure proposals. Evaluate and test emerging technologies (hardware and software) in close interaction with collaborators 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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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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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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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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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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, 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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to the development, adaptation, and application of machine‑learning models tailored to RODI data (in collaboration with project partners). Designing and implementing an innovative image‑based database to manage and
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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