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3.5-year D.Phil. Research Studentship in Lithium-ion and Sodium-ion battery electrolytes: Modelling and Characterisation Supervisors: Professor Charles Monroe and Professor David Howey Electrolytes
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To make reliable predictions and analyses of air pollution, data assimilation methods, which integrate observational data into model simulation to update the model state and the underlying
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support for the lab Job Requirements: Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or related field Knowledge and experience in world model, computer vision and deep learning
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responsible for generating and analysing data from lab-based activities. These activities will involve heterologous expression of fungal effectors in model yeast and plant systems. All work activities will be
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combines large language models, real-world data, behavioral science, and theory-driven modeling to build realistic and interpretable simulations for emergency planning and risk communication. The student
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, numerical modelling, data processing, and the preparation of research reports. Organizational Status Reports to the Professor and the Research Associate responsible for the project. Works collaboratively with
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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) investigates the chemistry and transport of trace substances in the troposphere. To this end, field and simulation chamber experiments as well as model simulations are conducted. Our research in the “Atmospheric
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recovery, using a sheep ovary model to develop clinically relevant protocols with the potential to improve fertility preservation for young cancer patients. Working alongside researchers with expertise in
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emphasis on FEA and reduced order analytical modelling. They will contribute to the EPSRC project Mechanics and Design of Kirigami-Based Energy Dissipating Devices led by Dr Martin Walker. In particular