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.
In addition to your application, please submit an up-to-date full CV, academic transcripts, at least one writing sample, and at last one presentation sample (e.g. slides or a link to a recording).
We consider ourselves to be a university where difference is celebrated, respected and encouraged. We have an excellent international reputation with staff from over 60 different nations and have made a positive commitment towards gender equity and intersectionality receiving a Silver Athena SWAN award. We truly believe that diversity of experience, perspectives, and backgrounds will lead to a better environment for our employees and students and encourage applications from all genders, backgrounds, and communities, particularly from under-represented groups, and value the positive impact that will have on the university. We are committed to maintaining a safe and secure environment for our students, staff, and community by reinforcing our Safer Recruitment commitment.
We're very proud to be a signatory of the Armed Forces Covenant. an accredited Disability Confident Leader; autism friendly university, committed to building disability confidence and supporting disabled staff.
Find out more about our benefits and watch the video to hear from our staff about what makes the University of Bath a great place to work as well as following us X and LinkedIn.
Be Well at Bath
We’re committed to creating a health-supporting working environment where everyone can thrive and be at their best. We offer a range of resources to enable you to do that from your first day here, including:
- Staff support groups and networks
- A network of Staff Wellbeing Champions
- A suite of tools, resources and frameworks that enable you to be at your best and thrive
Find out more about being at your best at Bath.
Email details to a friend
Further details:
Terms and Conditions of Employment
Right to Work in the UK: We do not assess immigration or right to work status until offer stage. Being invited to interview does not guarantee you are eligible for visa sponsorship and all offers are conditional on meeting right to work requirements. Further information is available on our application support webpage.
Anonymous shortlisting: We are constantly seeking to reduce the unconscious bias that enters any assessment process, with the goal of creating an inclusive and equal assessment process. To support this, personal details such as your name, may be removed from application forms at the initial shortlisting stage.