Job Description
We are seeking an ambitious, talented, and motivated individual to lead an exciting and innovative Knowledge Transfer Partnership (KTP) project between Control Station Ltd and the School of Built Environment, Engineering and Computing at Leeds Beckett University.
This 24-month KTP project will centre on the development of an advanced AI capability for CSL's existing Industrial Internet of Things (IIoT) system, creating a solution which will deliver advanced remote connectivity, AI integration and data optimisation for large, complex data sets - an innovative step-change in this sector.
The Role
Supported by a comprehensive project plan, you will work at CSL with professional engineers and with academics from Leeds Beckett University to
- Lead the design and implementation of an AI-driven risk reporting and management portal, integrating data from in-house remote monitoring systems and business intelligence tools to enhance Control Station’s service offerings.
- Prototype, evaluate, and compare commercial and open-source AI technologies, including LLMs, RAG and agent-based approaches to determine optimal solutions for real-time decision support…
- Facilitate technical integration and user acceptance testing, ensuring the AI system aligns with internal business processes and stakeholder needs, and is fully embedded within Control Station’s operational architecture.
- Conduct a comprehensive internal audit of Control Station’s resources and capabilities, identifying strengths, bottlenecks, and opportunities for competitive advantage using frameworks such as VRIO and RBV.
- Develop and maintain a secure, accessible Knowledge Repository, capturing all technical artefacts, project outputs, and process documentation to support long-term innovation and internal capacity building.
The Company
Control Station Limited (CSL), are specialist systems integrators, designers and manufacturers of control solutions. They integrate technology and engineering solutions for a range of control and access systems including safety-critical control panels for fire shutters, loading bay systems and aircraft hangar doors. CSL has an impressive UK and overseas customer-base, including Amazon, Ocado, the RAF, London Fire Brigade and Heathrow Airport.
The Person
We are seeking candidates with a strong academic background, holding at least a 21 degree in Software Engineering, Computer Science, or a closely related discipline. A keen interest in machine learning and artificial intelligence is also essential.
Applicants should be technically proficient, with experience in software development, embedded systems, or IoT technologies. You should also be able to demonstrate excellent project management and interpersonal skills. Familiarity with electronic control systems, software and programming tools and experience designing and developing user interfaces would also be advantageous.
This is an exciting role for the right candidate presenting an excellent opportunity to make a tangible difference to the business.
You will work in collaboration with an engaged and forward-thinking team at CSL as well as a team of academic experts from Leeds Beckett University to drive and deliver a 24-month project, through the acclaimed Knowledge Transfer Partnership (KTP) programme. KTP is an invaluable way to fast-track your career and gain wide-ranging and senior level experience.
The scheme provides excellent training opportunities as well as a generous budget to support your personal and professional development. The candidate will also have the opportunity to use the knowledge gained working on the project towards a higher qualification (MRes or PhD), with fees waiver, so if you want to add to your educational profile, this would be the perfect opportunity.
Information Session
If you would like to find out more about this role we plan to hold an online information session on Teams on 1400 – 1500 on Thursday 28th August. If you wish to attend this session, please email l.t.forester-green@leedsbeckett.ac.uk to register your interest.
For more information about this post, please contact Laura Forester-Green ( l.t.forester-green@leedsbeckett.ac.uk)
Closing date Monday 8th September 2025 (2359)
We welcome applications from all individuals and particularly from black and minority ethnic candidates as members of these groups are currently under-represented at this level of post. All appointments will be based on merit.
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