147 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation" Fellowship positions in Norway
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Positions Country Norway Application Deadline 1 Oct 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37,5 Is the job funded through the EU Research Framework Programme
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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 UiB - Knowledge that shapes society Through
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Norway Application Deadline 1 Oct 2025 - 00:00 (UTC) Type of Contract To be defined Job Status Negotiable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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may also apply and can be offered a position conditional on a satisfactory result. It is a requirement that the successful applicant is granted admission to the university’s doctoral programme in
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Environment at the Norwegian College of Fishery Science (NCFS), with an appointment for a duration of four years. The position is for a period of four years. The nominal length of the PhD programme is three
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to show a keen interest in multidisciplinary scientific research and innovation. Some knowledge of various sensing methods will be an advantage. Good knowledge in scientific programming is very useful
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the master's degree has been awarded. The candidate must have good knowledge in the topic of Cryosheric Processes. Proficiency in scientific coding and data analysis programming languages, such as Python
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the master's degree has been awarded. The candidate must have good knowledge in the topic of Cryosheric Processes. Proficiency in scientific coding and data analysis programming languages, such as Python
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. Proficiency in relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with
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requirement Strong programming skills applied to geospatial data, such as satellite data, is a requirement. Experience working with deep learning classification techniques applied to geospatial data is an