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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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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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on modelling and testing of new reactors with a view to optimising the best systems for mixing supercritical water (>378o C and 221 bar) with wastewater feed streams. This needs to generate residence times
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determine the impact of community acquired pneumonia that requires hospitalisation has on the quality of life of patients. The final stage will be to design a generic economic model to evaluate any new
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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functional motifs are encoded in HS chains and how they influence their biological activity. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids
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an assessment of the part quality; this will involve the development of laser beam processing on specific aerospace materials, and a model to understand the fundamental mechanisms of the process to identify
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop