About the Project
A fully funded PhD opportunity to participate in the world-leading research undertaken by the EPSRC Doctoral Landscape Award at the University of Sheffield.
Supervised by Dr Anton Ragni and Dr Daniele Tartarini.
The University of Sheffield is one of the leading Russell Group universities in the UK. We carry out cutting-edge research with strong links to industry. When you enrol to do a PhD with us, you will be working with world-leading academics and have access to top of the range facilities. As a PhD student you will have the opportunity to gain skills not only to conduct research, but also to take your career to the next level, whether you want to stay in academia, go into industry or the public sector, or set up your own company. You will have access to a range of training and support services to help you excel in your studies and beyond.
Project Description
In his recent announcement, the Prime Minister outlined an educational reform letting Year 10 school children to receive education in a range of subjects deemed critical for future, AI-driven, economy. The AI being both the subject and the key driver of the reform is a rather complex phenomenon. Not only is AI a relatively new subject of study (cfg physics), it is also a much less formally understood one (cfg. mathematics). Educational literature also lacks much, if any, knowledge on how to effectively educate students in AI.
These challenges, reservations and an occasional pushback however are not new. Not long ago it was programming that crossed the educational boundary of something only taught to a select few at universities and entered mainstream secondary, and sometimes primary, school setting. Somewhat unsurprisingly, traditional university teaching approaches had not succeeded and necessitated development of alternative ways of delivering a new kind of content. One such new way was Scratch developed by MIT (https://scratch.mit.edu/), an ecosystem for teaching and learning programming where programs are created by stitching together drag-and-drop blocks that represent basic programming concepts such as loops, events, mathematical operators, etc. The introduction of Scratch has had a profound impact on the ability of schools to deliver foundational programming education. No such ecosystem exists for teaching and learning foundational AI, however. Although it should be possible for schools to deliver either locally or centrally produced content on a range of AI themes, such as ethics, environment, large language models and even agents, the lack of foundational education behind such AI themes will make the vision of AI-driven economy unachievable.
This project aims to create a Scratch-like ecosystem for teaching and learning AI that will encompass key foundational topics of neural networks, layers, data, optimisation and scheduling. The project will build upon an early prototype of this ecosystem developed by Dr Ragni and his team. As a part of this project you will lead development of the ecosystem to incorporate features informed by interactions with stakeholders, organise outreach activities, and develop teaching and learning resources backed up by rigorous user studies. By the end of this project you will acquire industry-relevant skills in software engineering, deep understanding of foundational AI and strong background in conducting education facing research.
How to apply
Interested candidates are strongly encouraged to contact the project supervisors to discuss your interest in and suitability for the project prior to submitting your application.
Please refer to the EPSRC DLA webpage for detailed information about the EPSRC DLA and how to apply.
Applicants must ensure that they use the correct application form linked to the EPSRC DLA webpage and must submit an application for October 2027 entry. The form is unique to the EPSRC DLA. It contains the list of advertised projects from which to select, and three questions specific to the DLA.
The application deadline is 17:00 GMT 13 January 2027.
The majority of our DLA studentships will be allocated to candidates who qualify for Home fee status, in accordance with EPSRC funding regulations which place strict limits on international recruitment.
Funding Notes
The award will fund the full tuition fee and a maintenance stipend at the UKRI rate (currently £21,805 per annum) for 3.5 years, as well as a research grant to support costs associated with the project.