Human-Inspired Cognitive Control for Autonomous Robotic Manufacturing (Ref: SF-JO-2026)

About the Project

The ‘what’

This project will develop cognitive control architectures that enable robots to adaptively plan and execute complex manipulation tasks involving deformable materials.

The ‘why’

Unlike robots, human operators excel in handling variability and uncertainty by continuously adapting their actions. Embedding such cognitive capabilities into robotic systems is essential to achieving truly flexible manufacturing—reducing cost, improving productivity, and enabling rapid reconfiguration of production lines.

The ‘who’

Based at Loughborough University, you will join a multidisciplinary team with expertise in robotics, cognitive science, and AI. Supervision will involve leading academics in human-inspired robotics and intelligent control, with collaboration opportunities across partner universities and research centres. Industry engagement The research is co-developed with industrial stakeholders in composite manufacturing, ensuring relevance to real-world applications and providing opportunities for industrial placements or secondments.

Methodology

You will design hierarchical task representations and perception–action loops, combining learning from demonstration with reinforcement learning. The work will include both simulation and real-world robotic validation, with a focus on active sensing and decisionmaking under uncertainty.

Skills and development

You will develop:

• Advanced knowledge in AI, robotics, and control systems
• Skills in reinforcement learning and human–robot interaction
• Experience in translating theory into real-world systems

The project also builds communication, teamwork, and innovation skills essential for interdisciplinary research.

Career pathways

This PhD prepares you for roles in AI-driven robotics, autonomous systems, and digital manufacturing, as well as academic research careers.

Why Loughborough

You will be part of a vibrant research community known for excellence in robotics and manufacturing. Loughborough’s supportive doctoral training environment emphasises collaboration, mentorship, and impact-driven research.

Name of primary supervisor/CDT lead:

John Oyekan j.o.oyekan@lboro.ac.uk

Entry requirements:

Applicants should have:

• A first-class or strong upper second-class (2:1) honours degree (or international equivalent) in a relevant discipline such as: Robotics Mechanical Engineering Electrical/Electronic Engineering Computer Science / AI Mechatronics or related fields
• A Master’s degree in a relevant area is desirable but not essential for exceptional candidates

Core technical skills

Applicants should demonstrate some combination of:

• Programming experience (e.g. Python, C++, or MATLAB)
• Strong mathematical foundations (linear algebra, probability, optimisation)
• Experience with modelling, simulation, or experimental work
• Familiarity with robotics, control systems, or machine learning (depending on project)

Research potential and mindset

Successful candidates will show:

• Ability to work across disciplines (engineering + AI + materials)
• Strong problem-solving and analytical thinking
• Curiosity and willingness to tackle open-ended challenges
• Good written and verbal communication skills

English language requirements:

Applicants must meet the minimum English language requirements. Further details are available on the International website.

Bench fees required: No

Closing date of advert: 30 June 2026

Start date: 01 October 2026

Full-time/part-time availability: Full-time 3 years

Fee band: 2026/27 Band RB (UK £5,238, International £29,500)

Project search terms:

manufacturing engineering, Artificial Intelligence, Manufacturing Engineering, Computer Science, Robotics, Control Systems.

Email address Wolfson:

ws.phdadmin@lboro.ac.uk