72 data-"https:" "https:" "https:" "https:" "https:" "https:" uni jobs at Chalmers University of Technology in Sweden
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platforms based on bosonic modes, also called CV modes, such as microwave harmonic oscillators used to process quantum information. The project provides a rare chance to develop new theoretical and
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at any research group connected to the Nano Area of Advance at Chalmers. You find the full list of PIs of these research groups on the Chalmers homepage: https://www.chalmers.se/en/collaborate-with-us
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FieldPhysicsYears of Research Experience1 - 4 Additional Information Website for additional job details https://academicpositions.com Work Location(s) Number of offers available1Company/InstituteChalmers University
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your native language, Chalmers offers Swedish courses to help you settle in. Find more general information about doctoral studies at Chalmers here . Application procedure The application should be
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Chalmers University of Technology is host for a well-funded tenure-track Assistant Professor position in Data Driven Cell and Molecular Biology, in a vibrant, international, and outward-looking work
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Bachelor’s degree is accepted. The following experience will strengthen your application: Practical experience with radars, embedded systems, remote sensing data or integrated sensing and communication (ISAC
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, Chalmers offers Swedish courses to help you settle in. Find more general information about doctoral studies at Chalmers here . Application procedure The application should be written in English and attached
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activities. If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Find more general information about doctoral studies at Chalmers here . Application procedure
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information of two references. CV(Please follow the CV guidelines. ) Research statement (1-3 pages) Summary of previous research and main results. Outline of future research goals. For assistant professor
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with catalysis/photochemistry Programming skills using Python and MATLAB Analysis of complex scientific data through machine learning What you will do Plan experiments together with your supervisor and