EPSRC Industrial Doctoral Landscape Award (IDLA) Studentship in Robotics and AI

Award details

Humans rely on tactile sensing to assess the properties of materials in their surroundings. For example, when running our fingers over our hair, we instinctively adjust our movements—varying pressure, speed, and contact angle—to perceive texture, smoothness, or elasticity. This interactive process involves both sensory perception and behavioural control, as different exploration strategies can yield different sensory outcomes.

This project aims to develop a robotic system equipped with advanced tactile sensing and AI-driven decision-making to assess material properties through physical interaction. The research will explore the interplay between tactile data acquisition and robot behaviour, investigating how a robot can actively adjust its movements to improve material perception. Key challenges include integrating high-resolution tactile sensors with AI algorithms for perception, designing adaptive exploration strategies, and ensuring robust performance across diverse materials and interaction conditions.

The successful candidate will investigate these challenges through a combination of:

1. Tactile sensing hardware and data acquisition – Developing robotic fingertips capable of capturing fine-grained tactile information and building a database to record tactile data.
2. AI-driven perception models – Applying machine learning and probabilistic inference to interpret tactile signals.
3. Robotic control and interaction strategies – Designing behaviour policies that enable the robot to explore materials automatically.
4. Simulations and real-world experiments – Conducting tests in controlled environments and evaluating performance on practical tasks.

This research will advance robotic perception and interaction, with applications in material handling for manufacturing, assistive dressing in elderly care, and waste sorting in recycling plants.

The successful candidate will join the Robot Perception Lab led by Dr. Shan Luo within the Centre for Robotics Research at the Department of Engineering, King’s College London. Located on the Strand Campus in central London, our research focuses on robot perception using vision and tactile sensing—particularly how robots can perceive and interact with deformable objects that respond dynamically to external forces. Our group combines sensor technology, robot simulations, AI algorithms and real-world experiments to develop fundamental insights into robotic interaction with the physical world.

King’s is a leading university providing world-class teaching and cutting-edge research. We are ranked sixth in the UK for the quality and quantity of research activity (Research Excellence Framework, 2021). King’s has played a major role in many of the advances that shape modern life, such as the discovery of the structure of DNA and research that led to the development of robots, radio, television, mobile phones and radar. King’s continues to lead the way on research and pioneers new ideas to make the world a better place. We are seeking a highly creative and motivated applicant with a keen interest in doing research in robot perception and manipulation, with robot sensing, machine/deep learning and computer vision techniques.

We offer:

1. You will work at one of the world leading universities, and have the opportunity to work towards your PhD with a group of excellent scientists in Robotics
2. You will receive funding for the generous stipend and cover for the fees.
3. Access to robot facilities in the lab, e.g., UR5 robot arms, ABB YuMi dual-arm robot, multiple robotic grippers and many other robot platforms
4. Collaboration opportunities in both academia and industry including funded placements at the project partner Unilever R&D

Please contact Dr. Shan Luo (shan.luo@kcl.ac.uk) for queries about the project.

Award value

Stipend: Tax-free stipend of approximately £22,780 p.a. with possible inflationary increases after the first year.

The stipend is the minimum amount you will receive during the studentship, it is likely to be enhanced by the industry partner and this will be confirmed in a funding offer letter at the offer stage of the process.

Bench fees: PGR Research allowance from £1,000 p.a. to maximum £4,500 p.a.

Tuition fees: UK tuition fees 25/26 £5,006 per year or please note that there are a limited number of international fee waivers for international students available across the faculty.

Note: A UKRI fully-funded studentship will only cover what is listed below. Applications should be aware there may be other costs which will not be covered by the studentship, for example, visa fees, healthcare surcharge, relocation costs and COVID-19 related quarantine costs.

Eligibility criteria

1. Experience in writing scientific reports
2. Excellent communication skills in English (both writing and speaking)
3. A good attitude towards team working in an international environment
4. Solid background in computer programming (for example, Python, C++, Matlab)
5. Degree in Robotics, Engineering, Computer Science, or a related field
6. (Preferred) Previous coursework and/or practical experience in robotics and machine learning, especially in robotics (ROS, MoveIt etc.) and deep learning libraries (PyTorch, Tensorflow, etc.)
7. (Preferred) Previous coursework and/or practical experience with robot platforms
8. (Preferred) Solid background in mathematics

Application process

To be considered for the position candidates must apply via King’s Apply online application system. Details are available on the Department of Engineering website. 

Please apply for Engineering Research (MPhil/PhD) and indicate Dr Shan Luo as the supervisor and quote the project title in your application and all correspondence.

Please ensure to add the following code ERSRCIDLA in the Funding section of the application form.

Please select option 5 ‘I am applying for a funding award or scholarship administered by King’s College London’ and type the code into the ‘Award Scheme Code or Name’ box. Please copy and paste the code exactly.

The selection process will involve a pre-selection on documents and, if selected, will be followed by an invitation to an interview. If successful at the interview, an offer will be provided in due course.

Further information can be found at https://www.kcl.ac.uk/study/postgraduate-research/how-to-apply

Contact Details

Please contact Shan Luo (shan.luo@kcl.ac.uk) for queries about the project.

If you require support with the application process, please contact pgr-engineering@kcl.ac.uk.