Construction of Artificial Intelligence (AI) models of processes that govern space weather in Earth’s radiation belts to describe extreme events (Ref: NUDATA24/EE/MPEE/WATT)

   Faculty of Engineering and Environment

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  Prof Clare Watt  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Overview of the CDT

This project is being offered as part of the STFC Centre for Doctoral Training in Data Intensive Science, called NUdata, which is a collaboration between Northumbria and Newcastle Universities, STFC, and a portfolio of over 40 industrial partners, including SMEs, large/multinational companies, Government and not-for profit organisations, and international humanitarian organisations. Please visit for full information.

Project Description

Our 21st-Century society relies heavily upon electronic infrastructure, and this infrastructure is vulnerable to natural electromagnetic hazards known as space weather. The research field of space weather includes the natural variability of the plasma and electromagnetic environment of near-Earth space, and how it responds to the magnetic variability of the Sun. In particular, this project concerns the radiation belts that surround the Earth. This region encompasses the orbits of useful satellites that provide navigation, communications and a whole host of other services. The hazardous radiation environment of the radiation belts can vary in strength by many orders of magnitude in a period of a few hours, and our models require significant improvement in order to be able to accurately predict these changes.

This project will allow you to develop expertise in artificial intelligence, particularly in machine learning and data mining. Previous AI models of radiation belts predict the high-energy electron flux. You will instead focus on predicting the multiple physical processes at work in Earth’s radiation belts in order to capture extreme events we have not yet experienced during the space age. You will use a wealth of observations from multiple spacecraft missions such as NASA Van Allen Probes to create accurate data-driven models of variable electromagnetic processes in space and probe these models for undiscovered knowledge. Your new data-driven models will be combined with physics-based numerical models to further understand, and try to predict, extreme space weather events.


All training in skills and subject-specific knowledge will be provided: you will have access to taught Masters-level modules in artificial intelligence and space plasma physics, in addition to more general courses in software development and computing as required. You will be encouraged and financially supported to attend national summer schools in space plasma physics, and there are many opportunities to apply for international summer schools in space weather modelling, space plasma physics, or machine learning.


This project would suit an applicant with a background in physics, applied mathematics, computing or related fields. Our large and diverse research group at Northumbria provides a welcoming and supportive environment in which to conduct your research. We have extensive collaborations with UK and international partners, and you will have opportunities to visit other research institutions to collaborate on your project (e.g. in the US or Europe), as well as to present your research at national and international conferences.

Academic Enquiries

This project is supervised by Professor Clare Watt. For informal queries, please contact [Email Address Removed]. For all other enquiries relating to eligibility or application process please contact Admissions at [Email Address Removed]. 

Recruitment Event

You will join a strong and supportive research team. To help better understand the aims of the CDT and to meet the PhD supervisors, we are hosting a day-long event on campus on Monday 15th January 2024. At that event, there will be an opportunity to discuss your research ideas, meet potential PhD supervisors, as well as hear from speakers from a variety of backgrounds (academia, industry, government, charity) discussing both STFC and data science as well as their personal paths and backgrounds. Click here for details.

Eligibility Requirements:

  • Academic excellence i.e. 2:1 (or equivalent GPA from non-UK universities with preference for 1st class honours); or a Masters (preference for Merit or above);
  • Appropriate IELTS score, if required.

To be classed as a Home student, candidates must:

  • Be a UK National (meeting residency requirements), or
  • have settled status, or
  • have pre-settled status (meeting residency requirements), or
  • have indefinite leave to remain or enter.

If a candidate does not meet the criteria above, they would be classed as an International student. 

Applicants will need to be in the UK and fully enrolled before stipend payments can commence and be aware of the following additional costs that may be incurred, as these are not covered by the studentship.

For further details on how to apply see  

You must include the relevant advert reference/studentship code (e.g. NUDATA24/…) in your application.

If you are interested in more than one of the Northumbria-hosted NUdata research projects, then you can say this in the cover letter of your application and you can rank all projects you are interested in (e.g. first choice, second choice, third choice). You are strongly encouraged to do this, since some projects are more popular than others. You only need to submit one application even if you are interested in multiple projects (we recommend you submit your application to your first choice).

Deadline for applications : 31st January 2024

Start date of course :  23rd September 2024

Northumbria University is committed to creating an inclusive culture where we take pride in, and value, the diversity of our postgraduate research students. We encourage and welcome applications from all members of the community. The University holds a bronze Athena Swan award in recognition of our commitment to advancing gender equality, we are a Disability Confident Leader, a member of the Race Equality Charter and are participating in the Stonewall Diversity Champion Programme. We also hold the HR Excellence in Research award for implementing the concordat supporting the career Development of Researchers and are members of the Euraxess initiative to deliver information and support to professional researchers.

Computer Science (8) Mathematics (25) Physics (29)

Funding Notes

The 4-year studentship is available to Home and international (including EU) students and includes a full stipend at UKRI rates (for 2023/24 full-time study this was £18,622 per year) and full tuition fees. Studentships are also available for applicants who wish to study on a part-time basis in combination with work or personal responsibilities.


Watt, C.E.J.; Allison, H.J.; Thompson, R.L.; Bentley, S.N.; Meredith, N.P. ; Glauert, S.A. ; Horne, R.B. ; Rae, I.J.. 2021 The implications of temporal variability in wave‐particle interactions in Earth's Radiation Belts. Geophysical Research Letters, 48 (1), e2020GL089962. 10, pp.
Watt, C. E. J., Allison, H. J., Meredith, N. P., Thompson, R. L., Bentley, S. N., Rae, I. J., et al. (2019). Variability of quasilinear diffusion coefficients for plasmaspheric hiss. Journal of Geophysical Research: Space Physics, 124, 8488– 8506.
Bentley, S. N., Stout, J. R., Bloch, T. E., & Watt, C. E. J. (2020). Random forest model of ultralow-frequency magnetospheric wave power. Earth and Space Science, 7, e2020EA001274.

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