Are you interested in applying cutting-edge data-driven methodologies to a wide range of interdisciplinary fields? We are offering six fully funded PhD studentships, providing a stipend of approximately £26,000–£28,000 (net) annually. Potential PhD topics span all the research areas in the School of Engineering Mathematics and Technology at the University of Bristol. These studentships include a year of collaborative team-based training and leadership development. In return, successful candidates will contribute to supporting our Data Science MSc students; therefore, an enthusiasm for teaching is essential.

At the University of Bristol, we strive to build a culture of inclusion and empathy where people can be themselves at work, recognising the value that diversity of people, perspective and experience bring to our ability to innovate and to maintain our position as a leading research-intensive university.

Information on applying for September 2026 entry to follow later in the year.

Biography: Abhishek Bhatt

I worked at UMass Amherst as a Research Fellow at the College of Information and Computer Sciences. There I worked on the Modelling of Quantum Networks under the NSF Center for Quantum Networks. The project is available openly on GitHub as QuantumSavory. Prior to that, I completed my undergraduate degree in Electronics and Communication Engineering at IIIT Tiruchirappalli, India. I am interested in researching Quantum systems for applications in sensing, computing and communication. [Read More]

Biography: Alex Williams

I am currently pursuing a PhD in Data Driven Engineering and Sciences, in the school of Engineering Mathematics and Technology at the University of Bristol. I previously studied MEng Mechanical Engineering at Bristol, graduating with first class honours in 2025. During my undergraduate individual research project I explored the vibrational dynamics of arrows shot from a recurve bow, using finite difference modelling of partial differential equations. I am excited to broaden my skill set by exploring the world of data science and machine learning this year, building on what I have previously learned. [Read More]

Biography: Jason Mclaren

Hi, I’m Jason, I graduated with an MEng in Electrical and Electronic Engineering from the University of Bristol, where I specialised in quantum photonics and telecommunications. My Masters’ research focussed on exploring and simulating distributed Bragg reflectors with cavities, and investigating how apodisation (tapering) effects their behaviour. My research interests are on the applications of machine learning in the world of electromagnetism, and applying machine learning to quantum hardware. My general interests range from (and not limited to) gaming, electronics tinkering and an avid metalhead! [Read More]

Biography: Jens Friedel

I studied Physics at the Universities of Bayreuth and Göttingen, with a focus on nonlinear and computational methods. As a member of the Complex Systems Theory group at the Max Planck Institute for Dynamics and Self-Organization, I contributed to research on epidemiological modelling and opinion formation dynamics. Following the completion of my Master’s degree, I joined the doctoral program at this institution. My current work aims to strengthen my modelling capabilities, with a focus on improving understanding of global catastrophic epidemic outbreaks and social dynamics. [Read More]

First day of the new DTE

We’ve just had our first day of the new doctoral training programme in Data-Driven Engineering and Sciences. Welcome to Abhishek, Alex, Jason, and Jens! (Hopefully a couple more people to join slightly later.)

We had a great day co-designing the training programme with the students, and getting to know each other. Looking forward to the rest of the year!

Applying to the Data-Driven Engineering and Sciences PhD Programme

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. [Read More]

Isambard-AI: supercomputing at Bristol

Isambard-AI is set to become the UK’s fastest and most powerful supercomputer, purpose-built for AI research following build completion in Summer 2025. Designed to provide open-source intelligence, it will transform research and drive AI-led breakthroughs in critical areas like automated drug discovery and climate research. There is also significant potential to recycle its heat output for nearby infrastructure. Built in a climate-controlled modular data centre and backed by cutting-edge Hewlett Packard Enterprise and NVIDIA technology, phase one of Isambard-AI is already up and running, and despite only representing a small part of the overall machine, is currently the second greenest supercomputer in the world and the 128th most powerful. [Read More]