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We have 20 Dynamics PhD Projects, Programmes & Scholarships in Sheffield
Dynamics PhD Projects, Programmes & Scholarships in Sheffield
We have 20 Dynamics PhD Projects, Programmes & Scholarships in Sheffield
Machine tool dynamics-based digital twins for real-time monitoring of cutting tool conditions in smart manufacturing
Background. Smart manufacturing, a broad category of manufacturing that employs digital information, flexible skilled workforce training, and computer-integrated systems, has become the primary pathway for transforming and upgrading manufacturing industry in the coming decades. Read more
Revolutionising Smart Manufacturing with Digital Twin Technology (C4-AMR-Laalej)
This PhD project aims at addressing a critical challenge. real-time monitoring of cutting tool conditions in advanced manufacturing. Read more
An innovative data/system science and AI-based approach for nonlinear electrochemical impedance spectroscopy of battery cells/systems (S3.5-ELE-Lang)
Battery systems are the most challenging component in terms of costs, durability, weight, performance and safety in many applications such as drive-train of electric vehicles. Read more
Developing methods to reduce the quasi-static pressures generated by explosions in confined spaces (C4-MAC-Barr)
When explosives detonate in a confined space, repeated reflections of the initial shockwave on the walls and other obstacles lead to the development of a long-term quasi-static pressure (QSP). Read more
Physics-Informed Machine Learning for Blast Load Estimation from Structural Response (S3.5-MAC-Curry)
The loading and resulting deformation resulting from explosive detonations has wide-reaching effects on different people ranging from civilian populations in conflict areas to instances where accidents result in damage. Read more
Enhancing personalised medicine via ecosystems of digital mirrors (S3.5-MAC-Dardeno)
Digital mirrors – mathematical refinements of digital twins – are predictive models that simulate real-time states of physical systems and are recognised as crucial for personalised healthcare in the UK. Read more
Harnessing the Power of Time Delays in Dynamical Systems
Time delays are often seen as a source of frustration — missed connections due to delayed flights, disrupted online gaming due to communication lags, or instability of dynamical systems due to tiny control loop delays. Read more
Exciting Funded PhD: Durability of Seals for High-Pressure H2 Generation, Storage & Use - Shape The Future Of Clean Energy!
The University of Sheffield's Leonardo Centre, a world-leader in tribology, is seeking an enthusiastic and self-motivated PhD student to join a collaborative project funded by John Crane Ltd, one of the world’s leading providers of engineered technology. Read more
Spillover-free control of flexible beams using piezoelectric sensors and actuators (S3.5-ELE-Selivanov)
The need for precise control of flexible structures is more critical than ever. Whether it’s reducing the weight of next-generation aircraft, ensuring the stability of towering skyscrapers, or improving the energy efficiency of mechanical systems, advanced control methods are at the heart of these challenges. Read more
Digital Twin for Marginal Chatter Detection (C4-AMR-Dominguez-Caballero)
The global digital twin market, including manufacturing applications, is rapidly growing. Real-time monitoring, predictive maintenance, and process optimisation are driving this growth. Read more
A Novel Process Monitoring Solution for Composite Manufacturing (C4-AMR-Kerrigan)
While significant advancements have been made in composite part manufacturing, such as in producing large scale wind turbine blades, there remains a significant opportunity to enhance the precision and efficiency of the process. Read more
System Identification and Uncertainty Quantification for Smart Robot Control (S3.5-ELE-Jones)
For robots to successfully handle complex tasks, they must be able to interact with and adapt to the ever changing real-world environments they operate in. Read more
Bayesian calibration of multiphysics models for nuclear fusion (C3.5-MAC-Tsialiamanis)
Uncertainty is becoming an imperative aspect of modelling in various engineering fields. Uncertainty results in variance in the outcomes of experiments and, as a result, errors in the predictions of models, even though the models may have been calibrated according to actual data from experiments. Read more
Causal Machine Learning to Enhance Decision-Support for Engineering Populations (S3.5-MAC-Hughes)
It is well established that medical treatments can vary in their effectiveness from patient to patient, based on factors such as their age, socioeconomic status, and the other pathologies that may be affecting an individual. Read more
Performance guarantees for neural networks: The view from control theory (S3.5-ELE-Baldivieso Monasterios)
Integrating Neural Networks into the field of control systems has proved to be a promising area of research, offering potential benefits, including increased performance, scalability, and greatly enhanced adaptability. Read more
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