Accelerated Knowledge Transfer (AKT) Associate in Reinforcement Learning

The University of Bath is seeking an ambitious and highly motivated graduate to join an exciting Accelerated Knowledge Transfer (AKT) project in partnership with Synoptix Ltd.

About the role

Pan--Tilt--Zoom (PTZ) cameras capture detailed imagery of selected contacts, but this reduces awareness of the wider environment.  This innovative project will assess the feasibility of a reinforcement learning system that decides where the camera should point and when to zoom. It will balance searching for new contacts, tracking known contacts and maintaining situational awareness under uncertainty.

The capability will extend Synoptix's Synx-Lookout product beyond detection and tracking by adding autonomous attention allocation, contact prioritisation and camera control while continuing to run on edge compute. Development will use Synoptix's synthetic environment capability, followed by testing with PTZ cameras and edge hardware.

Whilst working on this unique project as an AKT Associate, applying your academic skills to an industrially focused project, you will broaden your knowledge and expertise, and be supported by both industrial and academic supervisors. 

The project will be supervised by Professor Özgür Simsek (Professor of Artificial Intelligence, Director of Bath's Reinforcement Learning Laboratory, Director of Bath’s Centre for Artificial Intelligence) and by George Leete (Senior AI Engineer at Synoptix Limited).

Synoptix Ltd

Synoptix is an award-winning engineering consultancy delivering advanced solutions across defence, aerospace, healthcare, energy and cyber security sectors. The company develops innovative AI-powered products including Synx-Lookout, an edge-computing maritime awareness platform that uses computer vision and autonomy technologies.

We welcome applications from candidates who have: 

• A BSc, MComp, MSc, or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science or a closely related discipline
• Practical experience with modern reinforcement learning algorithms using function approximation.
• Ability to manage workload independently and effectively.
• Strong written and verbal communication skills.
• Technical report writing experience.
• Intellectual curiosity and enthusiasm for research-driven innovation.
• Resilience and problem-solving mindset.

The Associate will investigate how reinforcement learning can be used to control PTZ cameras operating in complex maritime environments

The post will offer the following benefits:

• Valuable experience and highly transferable skills.
• Mentoring from the company and academic team.
• Access to University resources to complete the project.
• Experience working directly with a technology-focused industrial partner.

This AKT project is funded by UKRI through Innovate UK. This programme has been designed to create short-term collaborations between a university and business to deliver a rapid and targeted intervention to accelerate the development of an innovation project, with potential for significant impact on the business. AKT projects are delivered by graduates who benefit from the opportunity to work on a strategically relevant project within industry, whilst receiving support and guidance from university academics. More information about the Accelerated Knowledge Transfer programme can be found at: https://www.ktp-uk.org/accelerated-knowledge-transfer/

Further information

This is a fixed-term role for a period of 3 months, to start no later than 13 November 2026.

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