We are building a new cohort-based PhD programme that is based on a first year of high-quality training in research and leadership. We are aiming to recruit six students. You will be a team; you will work and learn together. We expect that you will come from diverse backgrounds across STEM (Science, Technology, Engineering, and Mathematics). So, when you are selected, we will work with each of you to provide your own personalised first year of training and research. This will open up the opportunity to do research in any area in which the School specialises — see our research groups on our website.
You each have different gaps in your knowledge and different ideas about where you would like to specialise. On this basis, we will recommend some existing units that you might follow. You will not be required to do exams or coursework like the other students on these units. Instead, we will give you small research-oriented tasks and mini-projects which are designed to test your understanding and prepare you for PhD-level research.
There will be some activities you do together. For example, we have the view that you will all need a grounding in Scientific Machine Learning (a relatively new field), and we aim to bring you together to do this, likely in the form of a journal reading club. There are also some core aspects of Large-Scale Data Engineering that you will need to learn, both for your research and to prepare you for teaching tasks later on — you will be learning these together as a group. Industrial/Applied Science problem-solving is another core activity in our school, and throughout this first year, you will be working together as a group with example problems brought in from potential academic supervisors and industrial collaborators to give you a rich interdisciplinary experience and exposure to a range of research-related problems.
The key aims for this first year are to help you create your future PhD project and to give you the best possible skills to take it forward. The first year will also include individual mini projects to try out different supervisors, broad leadership and teaching skills, and training in how to develop research questions into work programmes. These are key skills you need both for your own PhD and to supervise Masters-level students. This Masters-level supervision will be a key part of your teaching duties in this DTE programme.
The first year will conclude by us helping you develop your own PhD research project proposal and us helping you put together a supervisor team for it.
Our programme is 4 years in duration in total with funding provided throughout. At the start of year 2, your PhD research project will have been finalised, and years 2, 3, and 4 will progress similarly to a traditional 3-year PhD, but with some added benefits — specifically, although you will all very likely choose different areas of specialisation, you will remain a team that can support each other and can work together (for example, in the delivery of your teaching).
We believe this model — of a first year of training and exploration preceding the choice of research project specialisation — is by far the best way to do a PhD. Those of you who are familiar with the UK system will recognise that it is broadly the CDT (centre of doctoral training) model established by the UK funding agencies. Note that if you already have a very specific and well-defined idea of what PhD work you would like to do, or you have already determined which supervisor you would like to work with, this model is not for you. We are looking particularly for students who will spend the first year in exploration and potentially form new research directions and ideas that we had not previously anticipated. Also, we will be steering you to develop PhD research projects which are strongly interdisciplinary in potentially new and interesting ways.
Outline terms
The annual pay will be in the range £26-27k (net) for the 25/26 academic year, with the exact amount to be finalised once ongoing UK-wide pay negotiations are completed. Annual increases for subsequent years will follow standard UK research council rates.
The funding will be associated with a teaching requirement, and this together with the final pay rate will be described in a contract that you will be given when you are offered a place. The contract will oblige you to a total of 750 hours of teaching effort over the 4-year period of the programme. Note this 750-hour figure includes standard ratios of preparation time. We have not finalised the distribution of hours over the 4 years — it is still under discussion — but a possible distribution is 125-250-250-125, with lower amounts in first year to reflect your reduced experience and extra workload in getting up to speed with the programme, and in final year to give you extra time to complete your PhD.
Note — it will not be possible to withdraw from your teaching obligations without losing your entire annual funding. Similarly, unsatisfactory performance in teaching might lead to performance management proceedings which also could lead to the loss of your entire annual funding.
Your university fees are covered irrespective of your “home” / “overseas” student status. The transaction to pay them will be direct between the School and the University and will not pass through your bank account.
Finally, as part of the deal, you will be offered an enhanced RTSG (research training and support grant), which we plan to be £3k per annum. This fund will be managed in combination with your supervisors and the programme director — and for example, might be used to buy books, or small items of equipment, but is primarily to support your attendance at conferences to disseminate your research — a key part we believe of the PhD experience.
How to apply
The final programme name is still subject to approval by the university. As such, you will need to apply using the existing Engineering Mathematics PhD programme in our online catalogue and we will transfer your application to the new programme when it is fully registered.
Start your application from the Engineering Mathematics PhD webpage. Choose “Engineering Mathematics (PhD)” as the award type and “Apply for September 2025 start” as the start date.
- If you have already applied for a PhD in Engineering Mathematics as part of another studentship, choose a different start date and you will be able to submit a second application; we will fix your application start date at a later point.
You will be taken to the online submission system; enter your details and supporting documents as requested. For the proposed PhD supervisors, enter “Prof David Barton and Prof Eddie Wilson” — note, this is because we are the co-directors of the programme, not because we will be your PhD research project supervisors.
Notes on specific documents requested:
Supervisor suitability form: download the partially completed supervisor suitability form; complete this form (the four highlighted sections only) and submit with your application.
Personal statement: highlight your motivation for applying for this interdisciplinary programme in particular, and any relevant experience and/or skills.
Research proposal: submit a copy of this webpage.
Research training statement: submit a blank PDF.
Your referees should be academics who can comment on your academic ability and potential for research. Do not put down Prof David Barton or Prof Eddie Wilson as referees.
Selection process
The deadline for applications is 26 February 2025. After this date we will short list applicants based on your academic track record and relevant experience. Your application to our programme will be considered independently of any other PhD applications you have submitted to the University of Bristol.
All short-listed applicants will be interviewed in March/April with final decisions made shortly afterwards. If you are based in the UK, the expectation is that you attend an in-person interview and associated activities (travel expenses will be reimbursed). If you are based overseas, alternative arrangements will be made.
We look forward to receiving your application.
David Barton & Eddie Wilson
Co-directors of the DTE in Data-Driven Engineering and Sciences