Fixed-term: The funds for this post are available for 2 years.
We are seeking to appoint a full-time Post-Doctoral Research Associate (PDRA) to lead the design, evaluation and deployment of an AI-powered tutor within the Isaac Science and Ada Computer Science online learning platforms. This is an exciting position within a well-established and successful online STEM education project and a chance to make an immediate real-world impact with your work in this fast-developing and exciting new area in the education sector.
Isaac Science, developed by the University of Cambridge, and Ada Computer Science, developed in collaboration with the Raspberry Pi Foundation, use modern web technologies and evidence-based educational approaches to improve STEM education. The platform provides online learning resources to improve physics, mathematics, chemistry, biology and computer science teaching to students aged 11-18 and is used extensively by schools across the UK and internationally. The platform currently supports hundreds of thousands of students and teachers and receives millions of question attempts each month.
The successful candidate will lead a major new initiative to develop a Socratic AI tutor capable of providing high quality, pedagogically informed support to learners as they work through questions on the platform. The AI tutor will be designed to guide student thinking through hints, prompts and explanations while deliberately avoiding the disclosure of complete answers. The objective is to enhance learning, develop student understanding and strengthen problem solving approaches.
The work will include a review of existing AI tutoring and AI-assisted learning systems, including commercial products and research prototypes. The successful candidate will work alongside our dedicated software engineering team to design and implement a prototype AI tutor as well as collaborate with our content and education teams where they will undertake trials with partner schools, evaluate learning outcomes and user experiences, and contribute to the deployment of successful approaches at scale across Isaac Science and Ada Computer Science.
Research Environment
The PDRA will be based within the Department of Computer Science and Technology at the University of Cambridge, a world-leading centre for research and innovation in computer science, education technology and computing education.
The role will involve close collaboration with:
The Isaac Science and Ada Computer Science software engineering team
The Isaac Science content and education team
Colleagues at the Raspberry Pi Foundation developing content for Ada Computer Science
Subject matter experts and content developers across STEM disciplines
Researchers within the Raspberry Pi Computing Education Research Centre
Academic researchers in AI, learning sciences and STEM education
Teachers and schools participating in platform evaluation and trials
Members of the wider UK and international community exploring the responsible use of AI in schools
The successful candidate will have a unique opportunity to influence the future of AI-enabled learning while working within an established and highly successful educational project in a world-class computer science department.
Key Responsibilities
Conduct research into AI tutoring systems, generative AI, educational AI and related literature.
Evaluate existing commercial and research AI tutoring products and identify best practice.
Design frameworks for pedagogically effective AI-generated feedback and hints.
Lead the design of an AI tutor for Isaac Science and Ada Computer Science.
Work closely with software engineers to implement and test prototype systems.
Develop approaches to ensure AI-generated responses support learning without directly providing answers.
Design and conduct evaluations, pilot studies and school-based trials.
Analyse quantitative and qualitative evidence from platform usage and educational studies.
Disseminate findings through academic publications, conferences, reports and stakeholder engagement.
Contribute to grant proposals and future research initiatives where appropriate.
Collaborate effectively with academic, technical and educational partners.
Contribute to the wider research activities of the Department.
A complete list of requirements and desirable criteria for the role may be found in the further particulars document. Examples of the essential criteria for this role include:
A PhD (or be close to completion) in computer science, artificial intelligence, machine learning, human-computer interaction, education, learning sciences, educational technology, computing education or another directly relevant discipline.
Experience of educational technology research or development.
Experience designing or evaluating digital learning interventions
What we offer
Conduct impactful research in one of the most significant emerging areas of educational technology.
Shape how AI is used to support learning in schools.
Work with a highly experienced team of researchers, software engineers and subject experts.
Collaborate with leading organisations, including the Raspberry Pi Foundation.
Access established networks of partner schools ready to participate in pilot studies and evaluations.
Publish impactful research while contributing to a widely used educational platform.
Be part of a successful, long-running University of Cambridge project with a strong record of innovation and impact.
Contribute to teaching and mentoring activities within the Department where appropriate.
In addition, the University offers an excellent working environment, generous annual leave entitlement, membership of the USS pension scheme, extensive professional development opportunities and flexible working arrangements.
Appointment at the Research Associate level is dependent on the award of a PhD. This is a postdoctoral-level appointment, those who have submitted but not yet received their PhD will be appointed at the Research Assistant -Grade 5, which will be amended to Research Associate-Grade 7 once the award of the PhD has been conferred.
Further information
For more information about the platforms, please visit:
Informal enquiries are welcome and may be directed to: Professor Alastair Beresford [email protected]
Applications should include a curriculum vitae, a covering letter describing relevant experience and interest in the role and contact details for two academic referees.
Please quote reference NR50921 on your application and in any correspondence about this vacancy.
