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methods adjusting them to the needs of the project Post processing of the materials produced to characterize the functionalized particles Perform advanced characterization of the materials produced by SEM
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This PhD programme is multidisciplinary and cross-disciplinary building on applied mathematics and physics, technology and engineering—and the interplay between these. The programme has an applied
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. The successful PhD candidate will collaborate closely as part of an interdisciplinary team consisting of formulation scientists, microbiologists and computer scientists. As a PhD candidate at OsloMet, you will
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to the doctoral programme, grade B or above for the master’s thesis is normally required. The applicant must have expertise in at least one systematic and analytical methodology, such as: designing, running, and
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attachments along with certified translations in English or another Scandinavian language must be uploaded to JobbNorge. The following premise forms the basis for the post as researcher: The researcher will be
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or a related field with a focus on cognition such as anthropology, archaeology, biology, or cognitive science. For admission to the doctoral programme, grade B or above for the master’s thesis is
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well as candidates with a background in machine learning methods. The PhD programme will straddle the boundaries between the field of wave modelling and the general field of machine learning, and we will set up a team
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grade background, you may be considered if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to a PhD Programme either at the Faculty
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. Addressing housing-related health risks in the USA, Vietnam, Turkey, and Ecuador, the project integrates community engagement, data science, and computational modeling. The key objectives of ComDisp
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computational modeling. The key objectives of ComDisp are: • Identifying and understanding housing, air quality, and respiratory health issues in each case study. • Linking climate change models to housing