Research Associate in Software Ecosystems for Automated Feedback

About the role

This role offers a unique opportunity to lead the development of a software ecosystem focused on automated formative feedback, blending education research with software engineering. Building on the success of our prototype, which has already delivered feedback to students over 1 million times, you will drive the evolution of the system into a more scalable and flexible platform. The goal is to enable a broader community of educators, researchers, and developers to create, test, deploy, and assess algorithms that enhance automated feedback in education.

What you would be doing

• Manage infrastructure (e.g. CI/CD pipelines, AWS Lambda, GPUs for training and inference).
• Extend functionality (e.g. new utilities in Python, extending to languages such as Wolfram, Lean, Maxima).
• Build boiler plates, exemplars, documentation, tutorials.
• Develop AI workflows such as training LLMs on our data sets.
• Analyse our data sets to define new features and requirements.
• Host workshops and training sessions for the community.
• Advocate for good practice and build community guidelines.
• Evaluate the performance of algorithms for automated feedback.
• Disseminate the results of our research at conferences and in journals.

What we are looking for

• Experience building, deploying, and managing software systems that are used by a community of developers is essential.
• Experience in education research or education technology development is desirable.
• You are independent thinking, self-motivated, organised, and have a team-orientated work ethic.
• An understanding of diversity and inclusion in higher education is essential.

 For full details about the duties and requirements of the role, please see the Job Description.  

What we can offer you

• Be part of a great team on an exciting project that is having a growing impact in the education sector
• Work with the latest software technologies and in a progressive education institution
• Freedom and responsibility to work in a way that suits you
• Build your academic career at a world-leading institution
• Sector-leading salary and remuneration package (including 38 days off per year)

Further information

This position is fixed term and is expected to run until 31^st July 2026.

If you require any further details on the role please contact: Dr Peter Johnson – peter.johnson@imperial.ac.uk.

Hybrid working may be considered for this role. Staff working in roles that are suitable for hybrid working will normally be expected to work 60% of their time onsite. The opportunity for hybrid working will be discussed at interview.

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