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  Comparing ground- and space-based datasets with data science and unsupervised AI/machine learning techniques (Ref: NUDATA24/EE/MPEE/COXON)


   Faculty of Engineering and Environment

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  Dr John Coxon  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 https://research.northumbria.ac.uk/nudata/ for full information.

Project Description

Space weather is, broadly speaking, the way in which Earth is impacted by coupling with the Sun and its magnetic field. Many key impacts of space weather, such as communications blackouts or power outages, occur due to induced currents in ground-based infrastructure. The focus of this project is not to characterise those induced currents directly but instead to build a better picture of the currents which drive them.

The Sun's magnetic field interacts with and connects to Earth's magnetic field in a series of highly dynamic, time-varying processes. This leads to two distinct but interrelated electric current systems. One set of currents are driven down Earth's magnetic field lines (known as Birkeland currents), which in turn drive currents in the atmosphere (known as Hall and Pedersen currents). Although we understand the theoretical link between ground-based and space-based measurements, there has been little work exploring the correspondence between the two.

This project will enhance our understanding of how these processes impact the Earth's surface by comparing space-based measurements of the Birkeland currents with ground-based magnetometer measurements. You will use the AMPERE dataset, a space-based dataset with dual-hemisphere coverage providing approximately 13 years of data, in conjunction with ground-based datasets such as SuperMAG, a global collaboration of magnetometer networks. You will exploit a variety of methods in this project, from data science techniques to unsupervised machine learning approaches such as k-means clustering and self-organising maps, in order to explore the similarity between ground magnetometer data and space-based Birkeland current measurements.

This project is highly collaborative. You will work with colleagues ranging from neighbouring offices to institutions worldwide, as well as having regular one-on-one meetings with supervisors. You will present to colleagues, attending group seminars and conferences to hear about the latest results and talk about your own work. You will travel nationally and internationally as well as publishing work in leading journals.

We welcome students with degrees in related disciplines, including physics and computer science. Prior experience in solar-terrestrial physics is desirable but not a requirement. Prior experience in programming, particularly scientific programming, is similarly desirable. The preferred project language is Python. You will develop your experience in space physics and Python programming.

Academic Enquiries

This project is supervised by John Coxon. 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); or APEL evidence of substantial practitioner achievement.
  • Appropriate IELTS score, if required.
  • Applicants cannot apply if they are already a PhD holder or if currently engaged in Doctoral study at Northumbria or elsewhere.

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.

  • 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 https://www.gov.uk/student-visa. It is important that you read this information 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.
  • Costs associated with English Language requirements which may be required for students not having completed a first degree in English, will not be paid by the University.

For further details on how to apply see

https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/  

You must include the advert reference (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 the 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) 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.

References

Coxon et al. (2018), https://doi.org/10.1002/9781119324522.ch16
Coxon et al. (2019), https://doi.org/10.1029/2018GL081658
Shore et al. (2019), https://doi.org/10.1029/2019JA026543

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