19 computer-programmer-"https:" "https:" "UNIS" "https:" "https:" "https:" "https:" "UNIV" "Univ" Fellowship research jobs at UiT The Arctic University of Norway
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applicants submitting proposals with other institutions across Europe was less than 15%.) More details on our MSCA support programme are here: https://ic3.uit.no/news/ic3-msca-support If you secure funding
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applicants submitting proposals with other institutions across Europe was less than 15%.) More details on our MSCA support programme are here: https://ic3.uit.no/news/ic3-msca-support If you secure funding
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details on our MSCA support programme are here: https://ic3.uit.no/news/ic3-msca-support If you secure funding, you will join a large and friendly team of researchers passionate about doing cutting-edge
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submitting proposals with other institutions across Europe was less than 15%.) More details on our MSCA support programme are here: https://ic3.uit.no/news/ic3-msca-support If you secure funding, you will join
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details on our MSCA support programme are here: https://ic3.uit.no/news/ic3-msca-support If you secure funding, you will join a large and friendly team of researchers passionate about doing cutting-edge
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Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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Laws (LL.M.) in the Law of the Sea and Joint Nordic Master`s Programme in environmental law. The position is affiliated with the national research program Arctic Ocean 2050 . The position is a fixed term
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The position Department of Physics and
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propose a project to establish an in vivo experimental animal model to study IE. Our plan is to injure the aortic valves in live mice and intravenously inject staphylococcus aureus three days later. Within
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learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image analysis, that is medical images that evolve over