AI Innovation Lead (KTP Associate)

• 20 days annual leave (not including public holidays).
• Flexible working opportunities, including hybrid working for some roles.
• Generous pension scheme.
• A wide range of discounts and rewards on shopping, eating out and travel.
• A variety of staff networks, providing opportunities for social interaction, peer support and personal development (for example, Race Equality, LGBT+, Women's and Parent's networks).
• Recognition Awards to reward staff who go above and beyond in their role.
• A commitment to your development access to learning and mentoring schemes, integrated with our Academic Career Pathways.
• A range of generous family-friendly policies
  • paid time off for parenting and caring emergencies
  • access to menopause support in the workplace
  • paid time off and support for fertility treatment
  • and more

More details can be found on our benefits page: sheffield.ac.uk/jobs/benefits (opens in a new window).

We are a Disability Confident Leader (opens in a new window). If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.

We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience. Our University Vision (www.sheffield.ac.uk/vision) outlines our commitment to building a diverse community of staff and students that recognises and values the abilities, backgrounds, beliefs and ways of living for everyone.

The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university.

We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more. Find out more about our benefits (opens in a new window) and join us to become part of something special.

Applications are invited for a Knowledge Transfer Partnership (KTP) research associate to develop an intelligent weld fabrication platform that can be applied to fabrication projects supported by Building Information Modelling (BIM) and Industry Foundation Classes (IFC) digital twins, delivering market-leading insights to improve fabrication planning, decision-making and productivity.

This is a unique opportunity at the interface of academic research and industrial innovation to develop cutting-edge solutions. Based at Power System Services in Chesterfield, Derbyshire, the associate will work in close collaboration with the company to lead the development and industrial application of advanced AI and computer vision technologies within a commercially focused environment.

The role requires the associate to balance the demands of high-performance computing and advanced research with the practical constraints of industrial deployment. The associate will rapidly develop domain expertise, engage with market and customer requirements, take ownership of key technical activities, and work as an integral member of an established industrial team, supporting the adoption of new AI-driven methodologies and translating cutting-edge research into practical commercial solutions.

The successful candidate will be a high-calibre, technically driven associate with a PhD in computer vision or a closely related discipline, or equivalent industry experience. They will have strong hands-on experience in rapidly developing and deploying high-performance, technology-driven solutions, together with the ability to translate research and emerging technologies into real-world industrial applications. They will also benefit from a KTP Residential Training Experience at Ashorne Hill.

• Translate complex welding and fabrication challenges into robust AI and imaging solutions suitable for real-world industrial deployment.
• Investigate, develop and evaluate machine learning, imaging and emerging AI technologies to identify effective approaches for the project.
• Design, implement and test prototypes, algorithms and software, optimising solutions for real-time performance, computational efficiency, cost and industrial feasibility.
• Lead data collection, processing, analysis, and experimentation to train, evaluate, and validate AI models under realistic welding and fabrication conditions.
• Develop and implement a framework for effective data collection, processing, analysis and experimentation pipelines for bespoke application contexts.
• Study domain and user contexts to determine appropriate domain rules and logic to support the design and development of the solution.
• Develop domain expertise in welding and fabrication, engage with end users and stakeholders, and translate operational and market requirements into technical solutions.
• Take ownership of multiple parallel activities, including research, rapid prototyping, testing and market analysis, ensuring delivery against project milestones and timelines.
• Work closely with the industrial and academic teams to support the adoption of AI-driven methodologies, communicate technical developments, and demonstrate how AI can augment existing expertise and workflows.
• Document research and technical outcomes, contribute to reports, presentations and publications, and identify opportunities for innovation, intellectual property and commercial exploitation.
• Carry out other duties, commensurate with the remit of the post.

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.

Essential

Essential

Essential

Essential

Essential

Essential

Application

Desirable

Essential

Desirable

sheffield.ac.uk/cs

For informal enquiries about this job contact Dr Jefersson dos Santos, academic supervisor, at J.Santos@sheffield.ac.uk and/or Dr Suvodeep Mazumdar, academic lead, at S.Mazumdar@sheffield.ac.uk

It is anticipated that the selection process will take place within a month of the post closing. This will consist of a formal interview. We plan to let candidates know if they have progressed to the selection stage approximately two weeks after the closing date. If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process you can contact COM-Recruitment@sheffield.ac.uk

By applying for this role you are agreeing to share your information with Power System Services.

We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision (opens in new window).