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PhD Studentship: Haptic-based teleoperation with proactive and expressive robotic manipulators

Computer Science

Location:  UK Other
Closing Date:  Monday 30 January 2023
Reference:  SCI2117

Developing fully autonomous systems in realistic scenarios is still very challenging. Hence, having mechanisms that put the human in the loop is crucial. In physical human-robot interaction (pHRI) robots and humans collaborate over physical proximity and/or contact to solve complex problems, such as those encountered in industry 4.0 applications, rehabilitation, robot-assisted surgery, remote handling and inspection. 

This PhD studentship will undertake an ambitious programme of work to develop intelligent teleoperation systems, where people can use robots are avatars to reach remote spaces. This project aims to study the haptic modality to explore remote spaces better and convey touch interactions and explain robotic intentions to humans who control the robots. We are interested in developing machine learning and control methods to allow robots to adapt individually to their human partners and create personalised interactions. 

This will involve the identification and representation of human adaptation processes, skill modelling, and selection of appropriate actions and roles for enabling truly personalised collaboration. Special focus will be on the use of haptic and tactile data to demonstrate how touch interactions can further enhance the communication and interaction capabilities in collaborative robots. 

A fully-funded PhD studentship is available for an outstanding graduate with strong interest in robotics, machine learning and physical human-robot interaction. The selected candidate will take advantage of extensive training and career development opportunities and will benefit from excellent support to produce and disseminate original research contributions at leading international venues. The role also offers the opportunity to engage in international collaborations as well as working within ambitious and diverse team of robotics and AI researchers in both UK and Singapore. The candidate will have access to state-of-the-art equipment, software, and research facilities, including research space and several robots (including Centauro, Franka Emika, UR 3/5/16, iCub, KUKA iiwa, Haption Virtuose, Geomagic TouchX), sensors and computer vision equipment (including force and tactile sensors, motion capture system, stereo, RGB, thermal (IR) and NIR), as well as dedicated data storage and computational facilities suitable for doing world-leading research in deep and reinforcement learning.

Funding and Programme Details: 

The studentship will be supported by A*STAR Research Attachment Programme (ARAP), which is a collaboration between A*STAR and partner universities to provide research opportunities for PhD students at A*STAR Research Institutes. 

The student will be enrolled in a four year programme, and spend 2 years at University of Nottingham followed by 2 years at A*STAR Research Institute under the joint supervision of Dr Ayse Kucukyilmaz and Dr Yan Wu.

The studentship is fully funded. For the first two years spent in the UK, this includes the tuition fees plus full stipend, tax-free at the RCUK rate (minimum £17,668 per annum).

Awardees are provided with the following during their attachment in Singapore:

  • Monthly stipend of S$2,700
  • One-time airfare grant of S$1,500
  • One-time settling-in allowance of S$1,000
  • Housing subsidy
  • Medical insurance
  • Conference allowance
  • IT allowance

More details are available here:

Entry Requirements:

Applicants should have, or expected to achieve, at least a first-class or upper second-class BSc or MSc degree (or equivalent) in Computer Science, Engineering, or a related subject. Applicants with significant relevant non-academic experience are also encouraged to apply.

If English is not the candidate’s first language, they must provide evidence before the beginning of the studentship that they meet the University minimum English Language requirements (IELTS 6.0 with at least 5.5 in each element).

Applicants should have an excellent background in mathematics and software engineering, and should be committed to applying their research to real robotic systems interacting with people in challenging environments. Familiarity with machine learning, and hands on experience with robotics hardware as well as relevant tools and software for robotics is a plus.

Application Process:

Please send an Expression of interest with subject “PhD Studentship – ARAP” to and in PDF format, consisting of 

1) your CV and relevant links (Github, website etc.)

2) a cover letter

3) your transcript

Post interview, application should be made to the School of Computer Science through the MyNottingham system stating the supervisor name (Kucukyilmaz) and project title.

Informal inquiries about the post can be made to Dr Ayse Kucukyilmaz at and Dr Yan Wu at

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