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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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et al. 2022; Mainstone et al. 2018; Datry et al. 2016). Streams are often flagged as intermittent based on downstream flows, but where or how they dry is not known. Capturing the evolution of river
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comprehensive framework for modelling gravitational wave signals from precessing eccentric compact binaries across the full detector landscape, from ground-based instruments such as LIGO and Virgo through
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anthropogenic activities, as well as limitations of existing models in effectively integrating human data to quantify human influence. Foundation AI models offer significant potential due to their strength in
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that utilize imposed flows or chemical influences or electrical fields to manipulate an active drop’s motion, but a systematic first-principles-based analysis of these effects is severely lacking. This limits
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Project Description: This EPSRC-funded PhD project will investigate how next-generation electric and autonomous vehicles can operate as symbiotic agents within the urban ecosystem—intelligently
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into standardized features. Transformer-Based Risk Prediction: A central component of this project involves developing your own time-aware transformer model. This predictive back-end will be trained on world-leading
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: Deterministic modelling based on historical and modern data. Geoscience Letters, 8(1), p.20. Zorn, E.U. et al, 2022. Identification and ranking of subaerial volcanic tsunami hazard sources in Southeast Asia
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aims to design and study advanced porous solids, such as MOFs, COFs, zeolites, carbonaceous materials, etc., for: Selective CO₂ capture and separation from gas streams Adsorption-based cooling and heat
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seasonal-to-subseasonal forecasting ensemble in modelling and forecasting these processes. As datasets develop, there may also be opportunities to assess simulation skill of AI forecasts. For further