Mapping proton-scale waves in the solar wind with deep learning (Advert ref: NUDATA23/EE/MPEE/WICKS)

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

The solar wind is a collisionless turbulent plasma that is launched from the Sun and evolves as it flows out to fill interplanetary space. One of the great mysteries of the solar wind is how turbulence causes heating of protons and electrons without collisions between particles. The answer must be in the interactions of the particles with electromagnetic fields of plasma waves, but there are many complex processes that could occur. The purpose of this PhD is to investigate the plasma waves on the scale of the solar wind proton motions that could interact with protons and measure the proton and electron properties around these waves, to find a link between waves and heating. To do this, you will first identify waves and classify them as well as looking for clusters of features in the proton and electron distributions as measured by spacecraft in the solar wind. You will use Parker Solar Probe (PSP), Solar Orbiter (SolO) and WIND as data sources to create a labelled data set of waves using existing techniques. Deep learning will then be used to create an efficient neural network to identify waves from raw data. Nonlinear fitting and clustering will be used to identify features in proton and electron data and then all these data will be combined to look for trends in space and with plasma parameters to create a map of proton heating. You will find evidence for changes in heating as the turbulence evolves with distance from the Sun and other large-scale properties of the turbulence, such as the dominance of outward propagating waves over inwards, and the presence of shears in the flow. Other objectives could be to look at efficient processing of data onboard spacecraft for future missions, and understanding how best to use past missions (WIND) to inform new/future missions.

You will attend SolO instrument team meetings with Dr Wicks, gaining direct access to the mission instrument teams and experience of how ESA science missions are operated. We welcome applicants with a background in physics, applied mathematics, or other related disciplines. Prior experience in scientific computing or plasma physics is a benefit, but we will provide you with the requisite training to gain all the skills you need to do your project. Our research group provides a welcoming and supportive research environment with a wide range of stimulating research. We organise seminars, journal clubs and other group activities to support you to grow as an independent researcher. We will enable you to travel to international schools, conferences and workshops to learn, present your findings, expand your research network and be inspired by new perspectives.

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 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.

Eligibility Requirements:

• 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

How to Apply

For further details of how to apply, entry requirements and the application form, see

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

Please note:

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).

We offer all applicants full guidance on the application process and on details of the CDT. For informal enquiries, email Professor James McLaughlin ([Email Address Removed]). Please contact the Principal Supervisor of the project(s) [Email Address Removed] for project-specific enquiries.

Deadline for applications: 31st January 2023

Start Date: 25th September 2023