About the Project
People affected by stroke, SCI and MND will often experience physical impairments. Rehabilitation can be an expensive long-term process, mainly due to the volume of labourintensive therapies. Repetitive practice such as Activity of Daily Living (ADL), is key to successful rehabilitation with the extent of recovery directly linked to the amount of practice. Recovery is not possible in MND but monitoring, and even anticipating, progression will enable better support to be provided.
It is time-consuming and requires a high degree of consistency to observe individual performing activities and is subject to the Hawthorne effect. This can have an adverse influence on therapies offered, with treatments focused on what the therapist might see as important rather than what the individual thinks is important to live independently.
The proposed research would explore the computer vision to automate the ADL tasks. The aim is to analyse the video stream of individuals performing ADL and develop algorithms, which could measure the deviations by comparing it to a perfect execution (face-to-face with carers) of the same ADL. This would provide a detailed comparison of the task execution and tracking of the patients’ progress/deterioration over time. This would be beneficial to health practitioners for monitoring and diagnosis, and for patients and their family to understand treatment progress and condition.
The ideal candidate will have a good undergraduate degree (2:1 or above) in a relevant science, engineering or math discipline and ideally (but not essential) a good Master’s degree (merit or above). The candidate is expected to have a good programming skills (in C++/Python/Matlab), and keen interest in high-impact interdisciplinary research (Computer Science, Psychology, Health and Social Care) work. Experience of computer vision/machine learning research and familiarity with OpenCV/Caffe/VLFeat/Scikit-Learn tool are desirable. There are additional requirements (IELTS/TOEFL if not native) that must be satisfied. Please refer to the FAQ at https://www.edgehill.ac.uk/graduateschool/faq/.
Informal enquiries may be addressed to Dr Ardhendu Behera (Department of Computer Science) at [Email Address Removed]
Duties and Responsibilities:
Students will be expected to:
- Successfully undertake an initial programme of accredited research training.
- Undertake a PhD programme of research under the supervision of an appointed supervisory team.
- Enhance the research culture of the Department in which they are located, the Research Institute to which they are attached, and the University by participating in events, conferences and training.
- Successfully complete a programme of teacher training.
- Undertake up to six hours teaching a week or working with the Institute to which they are attached alongside University Departments or external agencies or organizations as directed by their Head of Department/Research Institute Director.
Eligibility:
- Candidates should have, or be expected to obtain, a good undergraduate honours degree level (2:1 or above) and/or a Masters level qualifications in a relevant subject area achieved within the last three to five years. If their most recent qualifications were obtained outside this period and/or they do not possess a Masters level qualification there needs to be convincing evidence that they will be able to make the transition to doctoral study.
- Although it is possible for candidates to apply for the GTA scheme more than once candidates who have applied unsuccessfully on two or more occasions are unlikely to be shortlisted for interview.
- International candidates who require a visa to study in the UK will need to demonstrate that they meet the requirements for a Tier 4 visa and possess appropriate English Language skills (IELTS Level C1/C2 or equivalent).
- Applications are not normally accepted from candidates who already possess a PhD, unless there are compelling reasons for doing so. If a PhD has been obtained in the UK as a Tier 4 (General) Student Visa holder, further sponsorship cannot be offered under the Tier 4 (General) Student Visa category, as this will not meet the academic progression requirements set by the UKVI.
How to apply
Applicants must complete the online application form, attaching one document containing:
- A ‘Research Proposal’ which should not exceed 2,000 words in length
- A full academic curriculum vitae
Selection Criteria:
Selection will be based on the following:
- Your curriculum vitae
- The synergy between your qualifications, research experience and declared research interest
- Performance at interview
- Supervisory capacity in the declared area of research
- Previous tutoring/teaching experience and related subject based qualifications
- The strategic and developmental needs of the Faculty
The Recruitment Process
Shortlisted candidates will be invited to interview and asked to give a presentation related to their research proposal. Successful candidates at interview will be put forward to a final selection panel which will make the decision on the award of the studentships. Candidates will not have to attend the final panel.
The closing date for all studentships is 5th May 2017
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