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Beyond head kinematics: a modelling and AI based tool for predicting effects of head impacts on the brain in sporting collisions


   Dyson School of Design Engineering

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  Dr Mazdak Ghajari  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Applications are invited for an exciting fully-funded PhD project on computational modelling of brain biomechanics in sporting head collisions, supervised by Dr Ghajari (HEAD lab, Design Engineering, Imperial College), Dr Chris Jones (SWA) and Dr Mike Loosemore (SWA, UCL).

This project will address the need to develop more accurate brain injury prediction tools that, along with instrumented mouthguards, can predict the effects of head impacts in sporting collisions in rugby union and combat athletes. There is significant evidence of head loading in sporting leading to long-term effects, such as the neurodegenerative disease chronic traumatic encephalopathy (CTE). Key questions are what type, level and frequency of the initial loading can trigger long-term effects. Recent advances in computational capabilities and mechanics of biological tissues have enabled studying the relationship between head loading and brain tissue damage by using detailed computational models of the human head. An example is the Imperial College Finite Element model of traumatic brain injury, which incorporates fine details of the brain anatomy, particularly sulci. This model has allowed us to predict the location of the CTE pathology. Advancement in technology has seen the rise of instrumented mouthguards, as a means of quantifying head impact kinematics sustained in a contact sport. The PROTECHT system (https://swa.one/, United Kingdom) is a new analytics contact load management platform, which embeds inertial sensors into custom-fit mouth-guards and provides real-time linear and rotational acceleration data. The combination of measuring real-time head impact kinematics of contact sporting athletes, detailed finite element brain modelling and advanced TBI assessment now enables us to address key questions in this field. This PhD project aims at answering two questions: a) how anatomical diversity can be incorporated in computational models of brain injury, b) whether data science approaches and real-world collision data can be used to develop real-time brain injury prediction tools.

Applicants should have, or expect to obtain, a strong Master’s degree in a quantitative STEM discipline, e.g., a 1st class degree in Engineering, Physics, Computing or any other relevant STEM subjects. A high 2:1 degree is acceptable if the applicant can demonstrate significant industrial or research experience and output. We also expect the applicants to have a demonstrable interest in research, innovation and inter-disciplinary research. It is desirable for the successful applicant to demonstrate experience, knowledge, and/or interest of relevance to the project, e.g., computational modelling, data science, programming, sporting injuries, etc.

Funding is available for both home and international candidates, but the tuition fees are covered at the home rate. Further information about fee status can be found at https://www.imperial.ac.uk/students/fees-and-funding/tuition-fees/fee-status/. The studentship is for 4 years and will provide full coverage of home tuition fees and an annual tax-free stipend of approximately £18,062 in 2022/23. 

Interested applicants should send an up-to-date curriculum vitae to Dr Mazdak Ghajari ([Email Address Removed]). Suitable candidates will be required to complete an electronic application form, following the standard Imperial College application procedure; more information can be found here. For queries regarding the application process, please contact [Email Address Removed].


Funding Notes

Funding is available for both home and international candidates, but the tuition fees are covered at the home rate. Further information about fee status can be found at https://www.imperial.ac.uk/students/fees-and-funding/tuition-fees/fee-status/. The studentship is for 4 years and will provide full coverage of home tuition fees and an annual tax-free stipend of approximately £18,062 in 2022/23.
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