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, using metabolic energy as the governing design constraint. The student will build on an established energy model for synaptic plasticity to derive theoretically grounded training schedules and will
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). The project investigates how machine learning (ML) can be used to enhance the modelling of boundary layers in industrial CFD simulations, where complex geometries and computational constraints limit near-wall
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We are recruiting highly motivated and enthusiastic doctoral students in the field of synthesis, characterisation and/or modelling of next generation materials for hydrogen storage and compression
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a comprehensive railway network delay propagation model capable of addressing a
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, and cost considerations. Aim To model and analyse component and system level reliability, availability and resilience of hydrogen systems. PhD project description The proposed project aims to develop a
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to create the next generation of modelling tools for liquid hydrogen (LH₂) fuel systems—a critical requirement for future hydrogen-powered aircraft concepts. This opportunity will drive advances in
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PhD project: Modelling Resilience of Water Distribution Networks Supervised by Rasa Remenyte-Prescott (Faculty of Engineering) Aim: To develop an modelling approach for assessing water network
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PhD project: Modelling Reliability and Resilience of Hydrogen Systems for Improved Safety and Sustainability Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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at the tumour margin represent a key target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing