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statistical methods (e.g. linear and generalized mixed-effects models, growth curve analysis and structural equation modeling). Familiarity with the opioid and endocannabinoid system and topics related
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. The project requires knowledge of real options analysis, quantitative modelling skills and understanding of the CCS value chain. The aim of the project is to: Develop methodologies to assess investment
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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aluminium alloys. The position is linked to the research groups SIMLab (Structural Impact Laboratory) and Nanomechanics. SIMLab's research encompasses experiments, modelling, and simulation of materials and
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electron microscopy analysis, Raman spectroscopy, fluid inclusion analysis, potentially appropriate petrochronological methods, and 3D geological modelling. The project will be conducted in partnership with
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a system for a real-time hydrodynamic and water quality simulations for selected zones in the coastal areas of the Ålesund municipality using data from installed sensors and remote sensing satellite
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prone to change and decline. One project component analyses and models the effects of climate-induced cryospheric changes on water flows. The other project component, to which you will contribute
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, and entrepreneurship. Doctoral Candidates will gain transferable skills and learn from industry role models, equipping them to make significant contributions to solving the AMR crisis. The succsesssful
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leader will be the Head of Department. About the project Modern control systems rely on being at least partially predictive while digital twins also must maintain a state model of the targeted cyber
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other are developing regulations that provides both incentives and constraints for the energy transition and emission reduction. The research objective of the PhD is to develop models that captures