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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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trends to provide immediate post-race feedback to Sport Directors that can be used to assess race strategy and tactics. Research, review and develop models based on objectives 1 and 2 to develop a race
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Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
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Project Overview The University of Sheffield, funded by the EPSRC and in collaboration with Shell, is offering a fully funded 4-year PhD studentship through the EPSRC Industrial Doctorate Landscape
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failure before components are built? We invite applications for a fully funded PhD project to develop microstructure-aware simulation models for fatigue and damage prediction in turbine wheels. Working in
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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon
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Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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vulnerable parts of the system for attacks, model faults and attack risks, and develop new control architectures that mitigates them towards achieving operational resilience throughout their life. Your PhD