Subject areas:
Mathematics, Biomedical and Life Sciences, Mechanical, Electronic and Information Engineering, Computer Science, Physics, Statistics, Data Science, Artificial Intelligence.
Funding type:
Research Training & Support Grant.
Stipend.
Tuition fee.
Modelling respiratory physiology during acute exposures to altitude to enable digital test and evaluation of future fast-jet environmental control and life support systems.
Award details
The last 20 years has seen a rise in so-called unexplained physiological events, which were a diverse collection of symptoms experienced by pilots in flight that had potential to interfere with their safe operation of the aircraft and with (potentially) uncertain aetiology. The likely cause of these physiological episodes are now understood to vary between aircraft platforms, and often can be explained with appropriate investigation of the aircraft, environmental control and life support system, and pilot experience. They are a diverse mix of historically recognised and understood conditions that can occur in flight such as hypoxia, hyperventilation, and acceleration atelectasis. Some of the contributing factors, however, were also a failure to appreciate the importance of some of the standards documents around ECLSS component and sub-system performance criteria that led to potentially compounding or synergistic effects to alter the expected breathing resistance or performance of the oxygen delivery system, which could impact the users physiology.
There had also been a collective international loss in aerospace medicine knowledge over the preceding decades that had contributed to uncertainty around their causation when they started to occur. This was compounded by a loss of connection between the aerospace medicine and engineering communities, which historically would have enabled a more informed response to this. As a result these events led to grounding of multiple billion-dollar fleets of military aircraft, especially in the US but also some other countries for prolonged periods of times at significant cost and loss of operational capability.
This has driven an interest in physiological monitoring but also a reinvigoration of aerospace medicine and physiology training internationally, and the need for closer interaction of this community with aerospace engineering. This collaborative approach across disciplines is now presenting opportunity for novel and innovative approaches, including the potential of Digital Twins to aid in the test and development of new ECLSS.
One area that is lacking in these efforts though is a respiratory model that adequately describes physiological responses to acute exposure to altitude and how these responses would be modified by ECLSS. Therefore, a core component of the work is to develop a next generation mathematical model of human respiratory physiology using up to date modelling techniques. Another key component is to use the model to assess the impact on physiology of different Digital Twin prototypes of the ECLSS to help test and refine system design and performance criteria prior to manufacture and testing of physical prototypes. It also presents opportunity for post event simulation to recreate the conditions around in-flight physiological episodes.
- 1st supervisor: Peter Hodkinson - Basic & Medical Biosciences
- 2nd supervisor: Ross Pollock - Basic & Medical Biosciences
- 3rd supervisor: Richard Whittle - Mechanical and Aerospace Engineering, UC Davis
Application Deadline: 04/06/2025 (applications can be closed earlier if a suitable candidate is found).
Award value
Each studentship is fully funded for 3.5 years. This includes tuition fees, stipend and generous project consumables.
- Stipend: Students will receive a tax-free stipend at the UKRI rate of £22,780 (AY 2025/26) per year as a living allowance.
- Research Training Support Grant (RTSG): A generous project allowance will be provided for research consumables and for attending UK and international conferences.
- Tuition fees: Home
Eligibility criteria
School of Basic & Medical Biosciences
Postgraduate research
Applicants should hold/be predicted a 1st class or upper second-class degree in relevant core subjects such as mathematics, mechanical, electronic, electrical and information engineering, computer science, physics, statistics, data science, artificial intelligence.
A 2:2 degree may be considered only where applicants also offer a Master's degree with Merit or above.
The successful candidate will work with world-leading experts in data science and physiological modelling, as well as exerts in human physiological responses to extreme environments and aerospace ECLSS engineers. The candidate will also test the efficacy of the model against data obtained from real lab experiments with human participants exposed to a variety of simulated altitude conditions.
Candidates who meet the eligibility requirements for Home Fee status will be eligible to apply for this project.
Application process
Please submit an application to the “DT4Health: Centre for Doctoral Training in Digital Twins for Healthcare” programme using the Admissions application portal via King’s Apply. Please include the following with your application:
- A PDF copy of your CV should be uploaded to the Employment History section.
- A 750-word personal statement outlining your motivation for applying for this research project should be uploaded to the Supporting statement section.
- References: Please insert contact details for two academic referees or relevant employers in research institutions/companies. Admissions will then contact your referees directly.
- Funding information: Please choose Option 5 “I am applying for a funding award or scholarship administered by King’s College London” and under “Award Scheme Code or Name” enter DT4H-PH.
Selection process
Shortlisted applicants will be invited to submit a 10-minute pre-recorded presentation. Further information about this part of the process will be provided by email.
The CDT team will review the presentations submitted and successful candidates will be invited to attend an interview.
Contact: