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information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/292175/phd-position-on-the-history-of-medical-plastics Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/292175
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Europe's leading universities, internationally recognized for high quality in research and education. As a societal institution, we shall contribute to sustainable and democratic development and be
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benefits and pension savings Career guidance and an individual career development plan Opportunity to take basic Norwegian language courses Research funds for travels and funding for conference participation
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leading universities, internationally recognized for high quality in research and education. As a societal institution, we shall contribute to sustainable and democratic development and be an attractive and
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. The objective of this PhD project is to develop AI methodologies for the analysis part of condition monitoring (CM) and predictive maintenance (PM). The primary challenge in predictive maintenance lies in
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opportunity to develop research projects involving several research groups at the faculty according to its strategy. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290045/researcher
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sustainability challenges. Furthermore, SolKit aims to develop essential knowledge and tools specifically tailored to address the conditions hindering the broad acceptance and deployment of BIPV technologies in
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of maturity, this technology requires to experiment a change of paradigm to guarantee a sustainable development for the years to come. One pathway to achieve this paradigm shift relies on the development
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or equivalent Skills/Qualifications Applicants must meet the following criteria: Be qualified for admission to the PhD program at the Faculty of Medicine, University of Oslo (https://www.med.uio.no/english
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leader is the supervising Professor, and your Line Manager is Head of Department. Duties of the position To develop methodology for risk assessment and modeling providing early warnings on the risk level