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the Section for Ethics and Health Economics (ETØK). The position is part of the project “Strengthening health and disease modelling for public health decision making”, funded by the Wellcome Trust. The project
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designing, developing and evaluating systems and models to enhance learning through AI technology. The PhD fellow will engage with developing and evaluating models and agents, as well as, multi-agent networks
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. Developing innovative separation processes is expected to positively impact the circular economy and enable Sustainable Business Model (SBM) innovation. The current project's goal is to contribute
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regulations that provides both incentives and constraints for the maritime energy transition and emission reduction. The research objective of the PhD is to develop models that capture the interaction between
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management, utilisation of natural resources, shipping, predictive modelling, or climate risk Core courses in optimisation, microeconomics, scientific methods Elective courses in operations research
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, shipping, predictive modelling, or climate risk Elements from the two tracks can be combined. For more information about the Department of Business and Management Science and its research profile, visit
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regulations that provides both incentives and constraints for the maritime energy transition and emission reduction. The research objective of the PhD is to develop models that capture the interaction between
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to ensure that the admission requirements are met, must be uploaded as an attachment. Main tasks Develop machine learning models to produce forest information at local and landscape scales Develop machine
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) at Norwegian University of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no
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seasonal emissions such as winter CH4 emissions, using AI tools to develop upscaling tools or upscale to circumpolar region, or using climate modeling such as the Norwegian Earth System Model to constrain