595 computer-programmer-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "https:" positions in Sweden
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to work on enabling groundbreaking, data-driven Life Science
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Sweden Type of Contract 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
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description To our institution, which conducts research at the highest international
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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 Description Chalmers University
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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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a background in Global Studies and/or Human Rights combined with expertise in Gender Studies More information about the bachelor’s programme: https://www.kau.se/en/education/programmes-and-courses
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core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as
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Sciences (BKV ). MMV and CSAN carry out research, undergraduate and postgraduate education within Health Sciences. The employment When taking up the post, you will be admitted to the program for doctoral
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time to your own studies. The doctoral programme comprises 240 credits for a Degree of Doctor and 120 credits for a Degree of Licentiate. The doctoral appointment is a paid position that offers a
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into operational decision‑support tools for farmers, in close collaboration with an industry partner. The project focuses on automated rumen‑fill assessment using 3D imaging, computer vision, and predictive