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high standards of software quality, reproducibility, version control, and documentation, supporting the transition of research developments into the operational model framework. The role involves close
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and AI-based approaches, including predictive modeling, stratification, explainable AI, and integrative multimodal analysis. The scholar will have opportunities to lead first-author publications
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Context: Controlling heat and particle fluxes on tokamak walls is a critical challenge for future tokamaks. Achieving burning plasmas near ignition while ensuring sufficient power distribution on divertor
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the relationship between whole-tree water use and wood cell formation in trees, using advanced growth models to predict the future of wood formation and carbon allocation in forests facing drier conditions. Within
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skills by providing high-performance perception, decision and control functionalities based on AI model outputs that are controlled to be dependable and trustworthy. The selected candidate will join the
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mathematics, computational physics, or a related discipline (PhD is advantageous) Experience with numerical modelling and analysis of large simulation datasets Knowledge of physical oceanography and experience
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to develop predictive models for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials
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working conditions? We welcome you to apply for a PhD position at the Department of Information Technology, Uppsala University. The Department of Information Technology holds a leading position in both
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together with other energy assets, such as electrical boilers, within a Model Predictive Control (MPC) framework that optimally balances electricity and heat production. Within FLEX-SMR, this PhD focuses
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of computational tools for process monitoring and predictive analysis Candidate Criteria Applicants should have: A PhD in Process Engineering, Chemical Engineering, or a closely related field Strong expertise in