|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||£17,668 full stipend, tax-free at the RCUK rate per annum|
|Placed On:||2nd February 2023|
|Closes:||1st March 2023|
Location: UK Other
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.
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:
More details are available here: https://www.a-star.edu.sg/Scholarships/for-graduate-studies/a-star-research-attachment-programme-(arap)
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.
Please send an Expression of interest with subject “PhD Studentship – ARAP” to firstname.lastname@example.org and email@example.com 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. http://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx
Informal inquiries about the post can be made to Dr Ayse Kucukyilmaz at firstname.lastname@example.org and Dr Yan Wu at email@example.com.
Type / Role: