European Molecular Biology Laboratory (Heidelberg) Featured PhD Programmes
University of Kent Featured PhD Programmes
University of Liverpool Featured PhD Programmes
University of Glasgow Featured PhD Programmes
University of Sheffield Featured PhD Programmes

KESS2 East PhD in Medicine: Use of technological platforms to enhance phenotypic understanding in primary dystonia


Project Description

This KESS2 East PhD project is aimed at recruiting a large cohort of individuals diagnosed with adult-onset primary focal dystonia, making use of state-of-the-art technology both in laboratory and real-life settings to better understand the motor and non-motor phenotypes.

Dystonia is one of the most common forms of movement disorder, affecting ~1% of the population and involves co-contraction of antagonistic muscle groups leading to abnormal postures and movement.

As a result, the disorder causes significant pain, disability and distress, impacting employment, education and social interaction.

In addition, individuals with dystonia also experience non-motor symptoms, which may include sleep disturbance, psychiatric symptoms, cognitive processing difficulties and pain.

In spite of this, motor and non-motor phenotypic understanding of dystonia is poor with non-motor symptoms often going unrecognised and untreated.

Previous work within our group has led to the identification of clear psychiatric phenotypes in genetically determined forms of dystonia, with this leading to interest in the wider spectrum of non-motor symptoms. However, adult-onset forms of dystonia represent the most common form of dystonia, and likely represents a highly heterogenous clinical group.

Aims and methods
To recruit a large cohort of patients with adult-onset focal primary dystonia.
To conduct detailed non-motor characterisation via our online portal – http://www.movementdisorders.wales
To apply the use of novel eye tracking and wearable technologies (with Aparito) to aid understanding of motor phenotypes in dystonia.
Determination of whether emerging technology in the form of wearable devices and smart phone apps can help to develop new digital biomarkers in dystonia.
Methods include:
longitudinal clinical studies, the use of different digital platforms to collect data relevant to patient phenotyping
data analysis skills to include R statistical analysis, MatLab and machine learning techniques
Commercial development linking with our partner company – Aparito – to understand the role of biotechnology in health sciences.
Opportunities
This project provides a wide range of outstanding opportunities that will be of use in future academic, industry or digital technology careers, as well as the platform for publication of direction setting data in this field.

You will have the opportunity to develop a range of key skills. These will include interacting with patients, both during assessments and with patient and public engagement activities, enabling the development of presentation skills to large, small, lay and professional audiences.

You will also develop a large skill set of data handling and analysis skills, including multiple software packages (R and MatLab), as well as the opportunity for machine learning based approaches. These are likely to be key skills in future academic and industry related careers.

Finally, a key element of this project is the opportunity to work alongside our partner company, Aparito. You will spend a period of time working within the Aparito organisation, observing the development of new software, as well as the process by which these are developed into successful commercially available products.

Funding Notes

Full UK/EU tuition fees
Doctoral stipend matching UK Research Council National Minimum

Eligibility criteria - Residency
Applicants for these awards must have a home or work address in the East area* of Wales at the time of their application for funding and enrolment.
Eligibility Criteria - Academic
Applicants should possess a minimum of an upper second class Honours degree, master's degree, or equivalent in a relevant subject.
Applicants whose first language is not English are normally expected to meet the minimum University requirements (e.g. 6.5 IELTS)

References

Applicants must:
have the right to work in the UK on completion of the scholarship
be classified as a ‘home’ or ‘EU’ student
satisfy the respective admissions criteria
It is a condition of eligibility for KESS2 funding that you have not applied for, nor are intending to apply for, a doctoral or research master's loan. Please read clause (3) (m) of The Education (Postgraduate Doctoral Degree Loans) (Wales) Regulations 2018 for more information.

*The East Wales region is comprised of 7 local authorities: Cardiff, Flintshire, Monmouthshire, Newport, Powys, Vale of Glamorgan and Wrexham.

In order to be considered you must submit a formal application via Cardiff University’s online application service. (To access the system click 'Apply Online' at the bottom of this advert)
There is a box at the top right of the page labelled ‘Apply’, please ensure you select the correct ‘Qualification’ (Doctor of Philosophy), the correct ‘Mode of Study’ (Full Time) and the correct ‘Start Date’ (July 2019). This will take you to the application portal.
If deemed suitable for the project, applicants will be invited to complete a ‘KESS2 Participant Form’ which assesses eligibility for funding. Applicants must also be able to provide supporting documentary evidence of their eligibility. Guidance on this requirement is outlined in the KESS2 Participant Form, an example of which can be downloaded as above. Suitable applicants will be sent this form to complete following the School selection process. Further advice is available from the KESS2 team.

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2019
All rights reserved.