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engineering programs and master's programs. More information is available on our website . This PhD project focuses on the development of plasmon-driven photoelectrocatalytic platforms for proton-coupled
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loading conditions. By generating datasets from finite element simulations, ML models can learn the mapping between unit cell design parameters and homogenised properties. State-of-the-art approaches
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Science, Engineering, Policy Analysis, Economics, Environmental Science) with demonstrated proficiency in coding and/or quantitative analysis. Interest in machine learning, computational modelling, systems thinking, and
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. This PhD proposal aims to develop an integrated modelling-prediction-control framework that uses extreme-weather-aware AI to coordinate frequency stability, voltage control, optimal power distribution, and
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as early indicators of anthropogenic and climate-driven change. However, limited understanding of the processes shaping species’ biogeographic distributions constrains our ability to predict ecological
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models (e.g., transformers, GANs) for text, image, or cross-modal data. -Familiarity with self-supervised learning and weakly-supervised learning techniques. -Familiarity with UAV technology or experience
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photovoltaics (PV) was identified by the IPCC as the technology with the highest potential among emission mitigation options. Scientific studies modelling energies scenarios for net zero emissions by 2050 project
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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the technical feasibility and performance of industrial heat pumps in steam generation and recovery. => Design options and technology inclusions Develop models to quantify the flexibility potential of electrified
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to neighborhood outcomes. In close collaboration with local stakeholders, experiments will be conducted to test model predictions and interventions. During the PhD, you will: Gain expertise in theory-driven