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.
About the Project
Deep learning is an increasingly common tool used in astrophysics, with the flexibility and speed of neural networks (NN) meaning they can be applied to a wide range of data intensive problems. For example, NNs have been developed to provide rapid estimates of the Sun’s atmospheric temperatures, helping to address major questions in solar physics, e.g., how is the corona heated to temperatures of over a million degrees? One key issue is that the current networks do not provide a measure of the result’s uncertainty, which is crucial for determining whether the answers provided by the NN are trustworthy. This is also of great importance in an industry setting, where a poor or incorrect answer could be dangerous or expensive.
During this project, the student’s goal is to develop NNs that incorporate uncertainty through the implementation of Bayesian approaches, which are currently at the forefront of deep learning research. The student would learn how to programme in Python and develop knowledge of the cutting-edge deep learning software (Tensorflow, Pytorch). Further, they would gain experience in the field of solar physics, working with data from NASA/ESA satellites. The developed networks will be applied to problems important in solar physics research (e.g., solar plasma temperature estimation, removal of data noise/corruption), with the opportunity to share work at scientific conferences in the UK and abroad. The student will also apply the skills learnt in an industry setting, undertaking a placement with our industrial partners.
Eligibility and How to Apply:
This studentship is available to home * and international applicants.
Please note eligibility requirement:
- Academic excellence of the proposed student i.e. first or 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 currently engaged in Doctoral study at elsewhere.
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. NUDATA/EE/MPEE/MORTON) in your application.
The NUdata CDT is offering multiple potential PhD projects this year. If you are interested in more than one of the offered projects, then you can say this in the cover letter of your application and then either [1] you can specifically indicate the other projects you are interested in, or [2] state you are happy to be considered for other projects in general. If you are shortlisted, we will then contact you to discuss these other projects. You are strongly encouraged to do this.
You do not need to submit a research proposal for the proposed project, since the project is already defined by the supervisor. If you have your own research idea and wish to pursue that, then this is also possible - please indicate this on your application (if this is the case, then please include a research proposal of approximately 300 words).
Northumbria and Newcastle Universities take pride in, and value, the quality and diversity of our students and staff. We welcome applications from all members of the community. We offer all applicants full guidance on the application process and on details of the CDT. For informal enquiries, email Professor James McLaughlin (Northumbria: [Email Address Removed] ) or Professor Tamara Rogers (Newcastle: [Email Address Removed] ). Please contact the Principal Supervisor of the project(s) for project-specific enquiries.
Deadline for applications: Friday 29th April 2022
Start Date: 1st October 2022
Funding Notes
Home and International students (inc. EU) are welcome to apply. The studentship is available to Home and International students, and includes a full stipend at UKRI rates (for 2021/22 full time study, this is £ £16,062pa) and full tuition fees. Also, additional funding is included to cover research costs and local, national and international travel such as conferences.
We have a limited number of International awards available.
* 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.
Further information about how UKRI classifies international fee status please see Annex B of https://www.ukri.org/wp-content/uploads/2022/04/UKRI-050422-TrainingGrantTermsConditionsGuidance-Apr2022.pdf
Applicants should be aware of the following additional costs that you may incur as these are not covered by the studentship.
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