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of design and innovation on value creation for stakeholders. For more information on D^3/LISH , please visit https://d3.harvard.edu and https://d3.harvard.edu/lish/ . Research Focus: Postdoctoral Fellows
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PhD Fellow in Anthropology: Bushmeat, Infrastructure and Zoonotic Risk in Africa–China Contact Zones
: https://uit.no/staffmobility Application Please note that the application will only be assessed based on the information submitted by the application deadline via Jobbnorge. It is therefore important that
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position see https://www.visual-intelligence.no/about/open-positions . We expect that you will engage in collaborative research with other members of the centre and the research group. You will collaborate
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combination of a STEM master’s degree and pedagogical education. Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system Good working knowledge of a
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and motivation for the position. Research experience and knowledge in climate physics and dynamics, Earth System interactions, future and paleo climate, and volcanic eruptions effects on climate and
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characterization of ferroic or related functional oxides. Knowledge of advanced functional materials, such as ferroic, magnetic, or multiferroic systems, or in energy-efficient cooling concepts is an advantage
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to knowledge exchange across partner institutions. The position offers a unique opportunity to contribute to the development of new modelling-based approaches for understanding systemic environmental risks in
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of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https://www.visual-intelligence.no/about/open-positions . We expect that you will engage in
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information about the Digital Security Research Group, see https://www.mn.uio.no/ifi/english/research/groups/sec/ . For more information about the Network and Distributed Systems Research Group, see: https
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the ability to grasp small and fragile objects without explicit prior knowledge of their models. Designing metrics to assess performance in assembly tasks, where robots connect diverse pieces together