A new magnetic field model for the environment of comets (Advert ref: NUDATA23/MPEE/GOETZ)

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

Comets are small bodies that journey through the solar system on often highly elliptical orbits. As they near the Sun, the ices on the surface sublimate and gas and dust escape into space. This is sometimes visible by naked eye as stunning cometary tails, but it also has consequences for the solar wind, the plasma permeating the solar system. As the cometary gases encounter the solar wind and its magnetic field, the two plasmas interact and form an intricate cometosphere. The European Space Agency’s Rosetta mission explored this region for over two years with the goal to understand the processes in this unique plasma.

The main goal of this project is to better understand the global structure of the magnetic field near a comet. Depending on the comet’s orbit and activity, the magnetic field can be drastically different, influencing the ions and electrons in the plasma and forming large structures like bow shocks. It is therefore important to have a reliable model of the magnetic field, so that we can 1) better interpret the results from plasma measurements and 2) predict the magnetic field at new comets.

The project will utilise a variety of methods to tackle this problem:

1. Analytical models. These models exist but are in need of updating. Small modifications to the physics contained in the model should be sufficient to provide a much better idea of the magnetic field near comets. However, the complexity of the model is severely limited by the availability of solutions.
2. Empirical models. A large database of measured magnetic fields at comets exists and is therefore ideally suited to form the basis of an empirical model. As part of this effort, the categorization of the plasma with the help of machine learning techniques is essential. This will serve as the foundation for the empirical model.

This project will be an integral part to the preparation for the European Space Agency’s Comet Interceptor mission and the student will have the opportunity to attend meetings with the mission and instrument teams and present their results at appropriate conferences.

Topics covered by the project are: space plasma physics, data analysis, machine learning, space missions, comets.

Student Profile: This project would be suitable for a student with a background in physics, applied mathematics or closely-related physical science. Prior knowledge of space plasma physics is not necessary. Prior knowledge of a programming language or machine learning is desirable but training in all necessary skills will be provided.

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
• 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

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).

Deadline for applications: 31st January 2023

Start Date: 25th September 2023