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for effective water resource management, climate modeling, and agricultural planning. Despite its importance, accurately monitoring evaporation remains a major scientific challenge due to the complexity
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operational performance. Based on feedwater composition (salinity, monovalent/divalent ion ratios, and valuable elements), you will model and design ED configurations that produce tailored concentrate streams
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enabling on-demand, local, and potentially circular production of spare parts — but effective decision-making frameworks are still lacking. In this PhD project, you will develop models and methods
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learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many incomprehensible model parameters that have been learned from data. For instance
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phase equilibrium modelling facilitate the prediction of metal budgets of crustal magmatic systems (e.g., Weller et al., 2024 JPet, Soderman et al., 2025 Nat Geosci). Pseudosections, the bespoke phase
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analytical facilities hosted at UU’s Electron Microscopy Centre. Project description Recent advances in thermodynamic phase equilibrium modelling facilitate the prediction of metal budgets of crustal magmatic
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to distributed energy resources, enabling energy sharing, reducing grid congestion, and enhancing sustainability. The PhD project will focus on the governance models adopted for energy hub platforms. These include
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appendages using the (halo)archaea as a model. Studying the infection mechanisms of archaeal viruses can provide insight into the evolutionary history of viruses and help to understand adaptation to extreme
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dialogue modelling), the series of experiments will result in four journal papers, to be integrated into a dissertation. You will participate in relevant conferences, workshops and seminars, and communicate
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responsibilities will include: Design and develop analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN