221 programming "https:" "https:" "https:" "https:" "https:" "Data driven Materials Modeling" Fellowship positions in Norway
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candidate will be admitted to the PhD programme in Science and Technology. The programme includes coursework, an independent research project culminating in a doctoral thesis, participation in national and
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’ educational programme . The PhD programme comprises a training component corresponding to 30 ECTS, amounting to one semester. In total, this means that 2.5 out of four years are allocated to working
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academically and professionally through organised research training. It is a condition that the person who accepts the position applies for and is granted admission to the Faculty’s PhD-program in Technology
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research fellow linked to the PhD programme in Humanities and the Arts . Please note: The call does not include PhD education within artistic research. Applicants who already has a PhD will not be assessed
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, macroecology, remote sensing, landscape ecology, pollination, and landscape modelling, aimed at understanding the past, present and future of alpine and mountain environments worldwide. The precise research plan
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degree has been awarded. A background in algebraic topology and Topological Data Analysis is required. Experience with scientific programming or algorithm development is an advantage. Applicants must be
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qualifications and the needs of the institute. The research fellow must take part in the faculty’s approved PhD program and is expected to complete the project within the set fellowship period. The main purpose
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requirement for all applicants to the PhD program. International candidates that are not exempt from the English language requirements pursuant to the guidelines of the Norwegian Agency for Quality Assurance in
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for admission to the IV faculty's Doctoral Programme (link), see Section 6-1 of the PhD regulations for more information. You must have a relevant Master's degree in Marine Cybernetics, Control Engineering
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is a requirement. Such experience may have been obtained through academic coursework, research projects, or professional employment. Experience with scientific programming using Python, R, Matlab