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Psychology
Location: UK Other
Closing Date: Friday 12 January 2024
Reference: SCI245
MRC AIM Doctoral Training Partnership
The AIM (Advanced Inter-Disciplinary Models) DTP is funded by the MRC between three Partners – the Universities of Birmingham, Leicester and Nottingham – and three more Associate Partners – the Research Complex at Harwell, Mary Lyon Centre and Rosalind Franklin Institute. We have a range of exciting and diverse PhD 4-year projects at all 3 partner Institutions which are now open for a September 2024 start and those available at The University of Nottingham are detailed below.
Projects with an industry partner (iCASE projects) offer a unique opportunity to undertake translational research and come with a mandatory placement requirement and an enhanced stipend.
Full information about funding of these projects and application details, including application form, plus Equality, diversity and inclusion form are available at https://more.bham.ac.uk/mrc-aim/phd-opportunities/ .
Application deadline
The deadline for submitting applications is Friday, 12 January 2024. Please ensure that your application is submitted with all required documentation by the above deadline as incomplete applications will not be considered. See full details at the “how to apply” section below. After the closing date, the project supervisors will review all applications submitted for their project and shortlist a maximum of two candidates for interview.
Shortlisted applicants will be contacted by 9 February 2024 via email. If applicants don’t receive an email by this date, then their application has not been shortlisted and they will not be invited for interview. Unfortunately, due to the number of applications the DTP receives, it will not be possible to provide feedback on unsuccessful applications.
Interviews
Interviews will take place during the week commencing 26 February and will be held via Zoom. Please ensure you are available for the whole week as we are unable to offer any alternative interview dates/times.
We strongly encourage you to contact the supervisor(s) of the project in which you are interested before submitting an application.
As stipulated by the funders, recruitment for International candidates to the DTP is capped at 30% of the whole cohort.
Academic requirement
Applicants must hold, or be about to obtain, a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in a relevant subject. A master’s qualification in a related area could be beneficial, as could additional relevant research experience.
More details can be found on the MRC website.
How to apply
Applications should include:
- A completed application form
- A CV consisting of no more than 2 sides of A4
- A transcript of module marks
- Completed ED&I form.
Please submit your application for University of Nottingham projects to [email protected] .
What happens after interview?
Candidates who are ranked highest at interview will be offered a place on the DTP and will be recommended for the PhD position. Successful candidates will then be sent details of how to make the formal application at the project host institution and will be subject to standard admissions checks which is standard procedure. The host institution admissions team will then send out formal offer letters and details of how to complete the registration process. The DTP Funding Team will send out formal funding award letters.
Projects open for application
School of Psychology
Project Title: Optimising patient selection for Deep Brain Stimulation in Parkinson's disease using multimodal machine learning (iCASE)
Supervisors: Mark Humphries, [email protected] , Dr JeYoung Yung (UoN)
Industrial Supervisors: Dr Jonathan O’Keefe (Machine Medicine Technologies Ltd (London) and St George’s Hospital, London. Parkinson’s clinical team led by Dr Francesca Morgante
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Parkinson’s disease has debilitating motor symptoms of tremor in the limbs, slowness of movement, and freezing, unable to move. A highly effective treatment is electrical stimulation deep in the motor regions of the midbrain. But surgery for this deep brain stimulation is only offered to around 2% of all patients, and about a quarter of those who receive it have poor outcomes. Optimising the selection of patients for deep brain stimulation will widen access to treatment, improve treatment outcomes, and prevent harm. The goal of this project is to test how fusing clinical data, neuroimaging, and video assessments could optimise the selection of patients. The project will be in collaboration with MachineMedicine (London), a MedTech company specialising in Parkinson’s disease, and the movement disorders clinical team at St George’s Hospital, London. The goal of the collaboration is to build an app used in-clinic for patient selection. MachineMedicine are leading the app development, building on their existing app for capturing movement video in-clinic. The clinical team at St George’s are running a trial of Parkinson’s patients to acquire the essential clinical data on patient symptoms, neuroimaging (including fMRI of spontaneous brain activity), and video capture of movements. In joining this collaboration, the PhD student will be trained in data-science and machinelearning tools, including how to extract and analyse MRI and fMRI data, in fusing data across modalities, and in developing a machine-learning pipeline for predicting patient outcomes. These predictions will be tested against the 12-month follow-up data from the St George’s trial patients. The student’s further training will include a 3-month placement at MachineMedicine, and visits to St George’s clinic.
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