About the Centre for Doctoral Training
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 https://research.northumbria.ac.uk/nudata/ for full information.
PhD project description
One of the biggest unknowns in near-Earth space is termed the Magnetospheric substorm, a sudden and rapid reconfiguration of Earth's magnetosphere leading to a substantial amount of energy transfer into the ionosphere and the creation of dynamic auroral displays in the Northern and Southern hemispheres. The major open question is what physical processes trigger substorms, generally thought to be a plasma instability in the magnetotail driven unstable via energy accumulation in the stretched magnetic fields and energised plasma. However, the substorm is thought to be initiated in a very small volume of 3D space, and our measurements are sparse.
High-resolution auroral observations of the evolution of the substorm onset arc are key to understanding this onset instability. “Auroral beads”, a travelling wave phenomenon along the substorm onset arc, are thought to be a projection of the magnetotail instability into the ionosphere, allowing the instability characteristics to be remotely sensed by using the ionosphere as a TV screen.
As part of a large, national consortium, Northumbria University have recently purchased 4 state-of-the-art auroral cameras due to deploy in Scandinavia in 2023. These auroral cameras will be used in conjunction with new radar capabilities from EISCAT_3D, modelling and in-situ spacecraft to pinpoint the onset region. You will use new and current missions such as the NASA THEMIS, Van Allen Probes missions and the new capabilities of imaging the Earth’s magnetosphere from the upcoming ESA SMILE mission to determine where substorm onset occurs and, critically, why.
This project is ideally suited to Machine Learning techniques for interested students. We would use pattern recognition in order to classify the required auroral bead forms. This will be done using multi-spectral convolutional auto encoders to identify and group similar observations. Following this, we will use normalising flows to learn the invertible mapping between energy flux observations in the magnetotail to those observed in the ionosphere.
We welcome applicants with a background in physics, applied mathematics, computer science or other related disciplines. Prior experience in scientific computing or plasma physics is a benefit, but we will support you to gain all the skills you need to do your project. You will get the opportunity to attend summer schools in space plasma physics in the UK and Europe to further your subject-specific knowledge, and we will support you to travel to international conferences to present your findings. During your PhD you will also get the opportunity to meet and discuss your work with space weather stakeholders, such as the UK Met Office, in order to explore potential benefits of your project beyond academia.
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 9th January 2023.
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.
- Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
- Appropriate IELTS score, if required.
- Applicants cannot apply for this funding if they are already a PhD holder or if currently engaged in Doctoral study at Northumbria or elsewhere.
Please note: to be classed as a Home student, candidates must meet the following criteria:
- 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.
- Immigration Health Surcharge https://www.gov.uk/healthcare-immigration-application
- If you need to apply for a Student Visa to enter the UK, please refer to the information on https://www.gov.uk/student-visa. It is important that you read this information very carefully as it is your responsibility to ensure that you hold the correct funds required for your visa application otherwise your visa may be refused.
- Check what COVID-19 tests you need to take and the quarantine rules for travel to England https://www.gov.uk/guidance/travel-to-england-from-another-country-during-coronavirus-covid-19
- Costs associated with English Language requirements which may be required for students not having completed a first degree in English, will not be borne by the university. Please see individual adverts for further details of the English Language requirements for the university you are applying to.
How to Apply
For further details of how to apply, entry requirements and the application form, see
You must include the relevant advert reference/studentship code (e.g. NUDATA23/…) 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 up to three projects you are interested in (i.e. 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 2023
Start Date: 25th September 2023