Location: | Nottingham |
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Salary: | £36,000 to £46,000 per annum, depending on skills and experience |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 10th September 2025 |
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Closes: | 16th September 2025 |
Job Ref: | SCI232425 |
University of Nottingham (UoN) invites applications for a KTP Research Associate in AI and Knowledge Systems to join our exciting collaboration with AEGIS Engineering Systems (AES) Limited (AEGIS). Based at AEGIS in London, you will report to the Head of Innovation and work closely with AEGIS’s Innovation team.
Fully supported by academic experts within the University’s School of Computer Science, including leading researchers from the Computational Optimisation and Learning (COL) and Cyber-physical Health and Assistive Robotics Technologies (CHART) research groups, you will lead a strategic project to develop an AI-powered knowledge capitalisation system (Prometheum) that combines the latest technologies in large language models and retrieval methods to enable engineering teams to access, structure and utilise organisational expertise efficiently.
As an enthusiastic researcher, this is a career-development opportunity for you to manage a Knowledge Transfer Partnership (KTP). Through the KTP, you will deliver a high-profile, commercially strategic project that will enable AEGIS to bring new, research-led knowledge essential for building a scalable, AI-driven system that captures, structures, and makes accessible the company's extensive engineering expertise. Through this KTP, AEGIS will embed capabilities in cutting-edge AI technologies, formalise internal knowledge capitalisation processes, and enhance its innovation capacity.
You will have the opportunity to demonstrate your ability to develop innovative solutions and communicate complex information to a variety of audiences within AEGIS and its stakeholders.
You should hold a Master’s or PhD (desirable) in Computer Science, Artificial Intelligence, Machine Learning or a closely related field. We are looking for a candidate who has experience in developing and deploying Knowledge Graphs, strong understanding of Language Models, (including retrieval-augmented generation techniques), software engineering practices (including agile development), and strong programming skills (Python preferred).
As a people-orientated individual, you will have the ability to influence and engage collaboratively with AEGIS, UoN and other stakeholders. As a proactive person, you will have the passion and desire for creating something new and be enthusiastic and motivated to organise your own time effectively and have a flexible approach to prioritising work tasks.
Throughout the KTP, you will be fully supported and mentored to nurture your talent. You will have your own budget of £2,000 pa for training and CPD, helping you develop your skillset and reach your personal and professional career goals.
UoN is committed to providing competitive employment packages whilst supporting the well-being of its staff to help them reach their full potential. As an employee of UoN, you will have access to the University’s resources and a range of benefits and rewards, including staff discounts, travel schemes and an attractive pension scheme.
KTP is a UK Government scheme promoting sustained and mutually beneficial relationships between universities and industry. This is a 24 months fixed-term contract and will be based at AEGIS Engineering Systems (AES) Limited, 138 Holborn, London EC1N 2SW.
Further information is available in the role profile. To apply for this vacancy please click ‘Apply Now’ to complete your details. Please upload a copy of your CV and Cover Letter with your application.
Working hours: (37 hours per week), typically, Monday - Thursday (7.5 hours) and Friday (7 hours), but flexible
Informal enquiries may be addressed to by email to: ender.ozcan@nottingham.ac.uk and marioramosgarcia@aegisengineering.co.uk. Please note that applications sent directly to this email address will not be accepted.
Interviews will be held in person in the UK. Location to be confirmed.
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