Hybrid AI Welding & Fabrication Lead

The University of Sheffield; Sheffield; On-site; GBP 39,000 - 42,000; Full time

Benefits offered by this job

20 days annual leave

Flexible working opportunities

Generous pension scheme

Discounts and rewards programs

Staff networks and development

Recognition awards

Development opportunities and Academic

Family-friendly policies

Job summary

The University of Sheffield invites applications for a Knowledge Transfer Partnership research associate to develop an intelligent weld fabrication platform using AI and computer vision within BIM/IFC contexts. Based with Power System Services in Chesterfield, you will bridge academic research and industrial deployment.

You will lead rapid prototyping, data pipelines, and collaboration with industry partners, translating cutting-edge research into practical commercial solutions over a 24-month

Qualifications

• PhD in computer vision or a closely-related discipline, or equivalent industry experience in manufacturing.
• Strong software engineering and data science capabilities.
• Experience of working directly with end users in deriving user requirements and conducting user evaluations.
• Ability to design & execute complex experimental workflows and conduct rigorous literature reviews.
• Ability to communicate technical findings effectively for both academic and industrial audiences.
• Evidence of leading research outputs, such as peer-reviewed publications or conference papers, appropriate to career stage.
• Experience in evaluating off-the-shelf tools and conducting market and technology scouting.

Responsibilities

• 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.

Skills

Software engineering

Data science

End-user collaboration

Experimental design

Communication of findings

Research outputs

Tool evaluation & scouting

Education

PhD in computer vision or related discipline

Job description

The University of Sheffield invites applications for a Knowledge Transfer Partnership research associate to develop an intelligent weld fabrication platform using AI and computer vision within BIM/IFC contexts. Based with Power System Services in Chesterfield, you will bridge academic research and industrial deployment.

You will lead rapid prototyping, data pipelines, and collaboration with industry partners, translating cutting-edge research into practical commercial solutions over a 24-month