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Deep Reinforcement Learning for Human-Robot Interaction

  • Full or part time
  • Application Deadline
    Friday, February 14, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

About This PhD Project

Project Description

Application details:
Reference number: QM/CO/2020
Start date of studentship: 1 October 2020
Closing date of advert: 14 February 2020

Primary supervisor: Professor Qinggang Meng
Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
Loughborough University has a flexible working and maternity/parental leave policy ( and is a Stonewall Diversity Champion providing a supportive and inclusive environment for the LGBT+ community. The University is also a member of the Race Equality Charter which aims to improve the representation, progression and success of minority ethnic staff and students. The School of Science is a recipient of the Athena SWAN bronze award for gender equality.
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Full Project Detail:
Human-robot interaction plays an important role in service robots and collaborative robots (Cobots) in manufacturing. Based on prior knowledge and sensory information, humans can easily understand the other person's movement intention during social or physical interaction. But this is a very challenging task for a robot even with the latest technology in AI and robotics. This project will develop a novel approach to learning such human-robot interaction skills based on the latest deep learning and reinforcement learning algorithms. It will investigate algorithms for some fundamental tasks in human-robot interaction such as human intention understanding, joint attention recognition and prediction of human movement trajectory. The developed approaches will be evaluated in simulation and, also by using a real robot like a Pepper robot.
This PhD project will be based in our newly refurbished Robotics and AI lab, equipped with intelligent mobile robots, humanoid robots, the latest deep learning computers and embedded systems, various cameras, LIDAR and other sensors as well as 3D printers. The PhD student on the project will join a team of several postdoctoral researchers and PhD students in deep learning, robotics and computer vision.
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Entry requirements:
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Computer Science or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: robotics, AI, deep learning, and computer vision.

Funding information:
This studentship will be awarded on a competitive basis to applicants who have applied to this project and/or any of the advertised projects prioritised for funding by the School of Science.
The 3-year studentship provides a tax-free stipend of £15,009 (2019 rate) per annum (in line with the standard research council rates) for the duration of the studentship, plus tuition fees at the UK/EU rate. This studentship is only available to those who are eligible to pay UK/EU fees.
Contact details:
Name: Professor Qinggang Meng
Email address:
Telephone number: +44(0)1509 635676

How to apply:

All applications should be made online at Under programme name, select Computer Science

Please quote reference number: QM/CO/2020

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