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plants with material co-production in energy system optimization models including, e.g., reservoir productivity predictions, novel surface processes for CRM extraction, CO₂ reinjection, and reconversion
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science and economics and finance. Leveraging its ‘4-in-1’ model of education and residential college system, UM provides all-round undergraduate education, nurturing talent to support social and economic
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learning (AI/ML) being a major focus. Many of the laboratory's interests center around the identification of small molecules using mass spectrometry data, and the use of language models to predict
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will build an experimental and computational platform based on 3D-printed, brain-mimetic tissue models with tunable transport properties, where interface transport can be measured and predicted
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, assess the health state of systems, and predict their future evolution and remaining useful life. The proposed approach integrates physics-based and data-driven modeling techniques, including machine
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, inspection histories, operational performance data, hyperspectral imagery, train-borne video analytics and satellite soil-moisture products to build predictive models of vegetation-driven and water-driven
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: Compiling and analyzing large erosion data sets (thermochronology, cosmogenic nuclides, suspended sediment, etc.); Statistical modelling of data to analyze drivers and make local and/or global predictions
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approaches treat NP design as static property prediction. This project takes a fundamentally different approach: using generative models to propose novel NP formulations and coupling them with explainability
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the preparation of a doctorate, contains: Hydrogeologists use numerical groundwater flow models for predicting impacts of climate change and pumping on groundwater and understanding and quantifying groundwater
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qualitative and quantitative analytical methods to model clinician attention, verbal reasoning, and documentation behaviour Develop and evaluate machine learning models, including unimodal, fusion, and