PhD Studentship: Contribution to Estimation and Control Designs for Constrained Impulsive Nonlinear Systems Applied to Tumour Growth Process

Impulsive control systems (ICS) have received great attention in the last decade in a wide range of applications, especially biomedical applications for which cancer treatment is a particular example. The tumour proliferation process is a complex, variable, and heterogeneous process that renders its control or eradication a challenge, opening doors to new avenues in cancer research and clinical oncology. A revolutionary new era in the field that aims to provide more effective treatment to patients is targeted personalized therapy. A key factor in personalized therapy is how drug schedules can be delivered in terms of amount, “how much,” and injection time, “how often and when,” to a given patient. One barrier preventing realizing clinical impact of this approach is related to the selection of a systematic therapeutic protocol for a particular patient. 

This project aims to propose a solution concept for modelling and controlling tumour growth process using tools from control and estimation theories. More particularly, you will be looking at a class of nonlinear ICSs for which there is still a lack of understanding and fundamental techniques on how to design optimal closed-loop controllers and estimators ensuring theoretical optimality guarantees. The designs become even more challenging when constraints on the impulsive input (e.g., positivity) and measurements (e.g., sparsity) are present, which is the case for cancer therapy. So, this research project proposes to contribute to the theory of impulsive control and estimation designs for a particular class of nonlinear systems with constraints on the input and output signals. A particular interest and emphasis of the project will be on applying the developed techniques to the problem of controlling the tumour growth process using a biologically grounded model that has shown success in clinical oncology.

This project is expected to strongly benefit both oncology and control theory fields, and you will have a unique opportunity to contribute in developing a rethinking of how the treatment is administrated in oncological clinics. You will join vibrant groups with PhD students, post-docs and academics in the Digital Health and Biomedical Engineering, and Cyber Physical System groups who are working on wide range of topics including control, modelling and data analysis of biomedical and cyber physical systems. You will have the opportunity to discuss your findings with medical experts and oncologists from Memorial Sloan Kettering Cancer Centre in New York, and Cancer Sciences Research Group at the University of Southampton. 

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date  31 August 2023 for standard admissions, but later applications may be considered depending on the funds remaining in place.

Funding: For UK students, Tuition Fees and a stipend of £17,668p.a. for up to 3.5 years.

Applications should include:

Cover letter

Curriculum Vitae

Two reference letters

Degree Transcripts to date

For further information please contact: feps-pgr-apply@soton.ac.uk

Advert information