709 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "INESC TEC" positions in Norway
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. The position will also focus on developing 3D imaging technology for nerve and synapse detection in tissue samples from tumors. The candidate will study the presence of synapses between breast cancer cells and
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This PhD programme is multidisciplinary and cross-disciplinary building on applied mathematics and physics, technology and engineering—and the interplay between these. The programme has an applied
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Engineering within three months of your employment contract start date, and that you participate in an organized doctoral programme through out the period of employment. The position is conditional on external
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through the “Arctic MSCA-PF program”. Successful postdoc candidates will be invited for a two-day MSCA-PF symposium June 10-11, 2026 (hybrid physical/digital event, see details at https://uit.no/arcticmsca
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are particularly suitable for a PhD education. You must meet the requirements for admission to the doctoral program from the Faculty of Engineering (https://www.ntnu.edu/studies/phiv ) You must be
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Deadline 8 Mar 2026 - 23:00 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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applicants for a PhD Fellowship in Physics/Computer Science at the Faculty of Science and Technology, Department of Mathematics and Physics. The start date is flexible, but not later than September 2026
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with regard to health, climate change and the resource base. The Department of Energy and Process Engineering is one of eight departments in the Faculty of Engineering. Where to apply Website https
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-erklæringen var sist oppdatert 28.12.2025 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan inneholde
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cookie and refresh page to watch video, or click here to open video) About the position Distributed machine learning takes advantage of communication and distributed computing to utilise distributed data