Funded Opportunities at NDCN
Mabel Churn Scholarship in Ophthalmology
Every three years, St Cross College plans to invite applications for the Mabel Churn Scholarship from successful applicants normally resident in the UK who have an offer to begin studying at the University of Oxford for a DPhil research degree in the Nuffield Department of Clinical Neurosciences (NDCN) in any area of retinal research. Please follow the link above to find out when the College next plans to recruit.
Oxford-MRC Doctoral Training Partnership iCase studentship
NDCN would be the host department for the fully-funded, 4-year DPhil project 'Development of a semi-automated CT-brain analysis tool for application to real world clinical cohorts' under the supervision of Professor Sarah Pendlebury. This is one of 17 candidate projects in the running for one of 8 Oxford-MRC DTP places for October 2024 entry. Find out more about the Oxford-MRC DTP scheme and how to apply, or read more about our NDCN project within the scheme.
if you also want to apply for an open/standard dphil place
Applicants will not automatically be considered for a standard DPhil place if not successful for the iCase project, unless they make explicit on their application in the ‘Proposed field and title of research project’ that they are applying for both the iCase and the standard DPhil with a project of their own; they must then also submit whatever standard documentation required for an application to the DPhil in Neurosciences (including a research proposal). Should they be shortlisted for both, they would need to interview for both the iCase project and the standard DPhil place separately.
oxford health brc phd scholarships in brain technologies
We are pleased to invite UK applications for a doctoral degree within the Oxford Health Biomedical Research Centre, in the Department of Psychiatry and Nuffield Department of Clinical Neurosciences of the University of Oxford. The doctoral degree will start in October 2024.
The BRC aims to bring together researchers from across the fields of health and science to improve the translation of research findings into clinical practice. The Brain Technologies theme specifically focuses on using innovative technologies to improve understanding, diagnosis, and treatment of brain disorders. This includes research into neuroimaging, neurostimulation, neuropharmacology, and cognitive neuroscience.
Both projects would be a collaboration between the OHBA (http://www.ohba.ox.ac.uk) and FMRIB (http://www.fmrib.ox.ac.uk), both of which are part of the Wellcome Centre for Integrative Neuroscience (WIN - https://www.win.ox.ac.uk).
The focus of the research will be on developing methods to support brain technologies in healthcare. Two potential projects are offered:
Project 1 – Assoc. Prof. Ludovica Griffanti, Prof. Steve Smith, Prof. Tom Nichols
This project will deliver new software tools for assessing brain health. This requires innovative methods for accurate and quantitative assessment of brain scans from an individual patient. This technology could be used, for example, to predict whether someone with memory decline is likely to go on to develop dementia.
Millions of hospital brain scans are performed globally each year. At the moment, these scans are interpreted by eye. But even the most expert clinician may not be able to detect subtle changes in this way. In the research setting, we build powerful algorithms that analyse information objectively, compare scans across individuals or over time (https://pubmed.ncbi.nlm.nih.gov/21979382/). However, these tools are mostly designed to analyse homogeneous data from groups of participants in research studies rather than to inform clinical decision making about individual patients based on variable clinical data.
This PhD project focuses on the steps needed to deploy such brain-health markers to support individual patient decision making in clinical practice: develop methods to obtain comparable measures from scans acquired with different hardware; model population variation in the measures and derive population norms against which to compare individual patients; mine population datasets (like the UK Biobank - https://pubmed.ncbi.nlm.nih.gov/27643430/) to identify subgroups within and across diagnostic categories. Ultimately, the tools developed could be used, for example, to predict based on a brain scan whether an individual with memory problems is likely to go on to develop dementia. Students will need good mathematical, engineering and computing skills, and through the project will acquire a strong set of skills in the areas of image processing, big data analysis, normative modelling, AI and machine/deep learning.
Project 2 - Prof. Mark Woolrich, Prof. Tim Denison
This project will develop new technologies for inferring brain activity in real world settings. These technologies could be used, for example, to detect changes in brain activity during sleep, that could predict development of neurodegenerative disease.
We use cutting-edge laboratory methods, such as magnetoencephalography (MEG) and high-density electroencephalography (EEG). We combine these data with state-of-the-art artificial intelligence and deep learning techniques to learn how the brain’s dynamics are organized into spatio-temporal patterns of fluctuating brain networks (https://pubmed.ncbi.nlm.nih.gov/36041643/). This approach allows us to detect early signs of brain network dysfunction in diseases such as dementia before symptoms show. This project is focussed on adapting these approaches for use on portable, low-density EEG data that can be acquired in real world settings, e.g. at home. This technology could be used, for example, to detect early signs of neurodegeneration in high-risk individuals based on changes in brain activity during sleep, or as part of a closed-loop system delivering brain-activity-cued brain stimulation.
This project requires the development and use of artificial intelligence (AI), machine learning and deep learning techniques. Students will need good mathematical, engineering and computing skills, and through the project will acquire a strong set of skills in the areas of image and signal processing, Bayesian inference, AI and machine/deep learning.
details of funding package
The scholarship funds a tax-free stipend, plus course fees at Home/ROI rates, plus financial support for research expenses, conference attendance, and consumables. The stipend will amount to not less than £18,622 per year for 3 years; this amount may increase each year but will definitely not decrease. This scholarship is supported by grants from the Rosetrees Trust and National Institute for Health Research Oxford Health Biomedical Research Centre (BRC).
Applicants should have at least an upper second-class honours degree in a relevant subject area and previous research experience. Education to Master’s degree level is highly desirable. Fees will cover Home rates only (not overseas rates).
how to apply
Potential applicants are asked to contact the supervisors named above as a first step to discuss their application. You are advised to do this well in advance of the application deadline. You will require supervisor support in order to submit an application that we are actually able to consider. As the project proposal you will need to write about your proposed approach/focus within the remit of the advertised position you have picked.
If you have supervisor support to submit an application then you will need to apply for this funded programme via the main University online graduate application form and pay an application fee of £75. The application form, all supporting materials required for the programme (including references) and payment must be submitted by the appropriate studentship deadline. To access the application form and application guide please visit our website at www.graduate.ox.ac.uk/apply. You must quote studentship code RT24NDCN as part of your application in the relevant field.
Deadline for submission of applications: Friday 1 December by 12.00 noon (UK time)
Studentship Code: RT24NDCN
Interviews will be held in January 2024 in Oxford or online during the week commencing Monday 22 January.
if you also want to apply for an open/standard dphil place
Applicants will not automatically be considered for a standard DPhil place if not successful for this scholarship, unless they make explicit on their application in the ‘Proposed field and title of research project’ that they are applying for both the Rosetrees/BRC project and the standard DPhil with a project of their own; they must then also submit whatever standard documentation required for an application to the DPhil in Neurosciences or Psychiatry. Should they be shortlisted for both, they would need to interview for both the Rosetrees/BRC project and the standard DPhil place in either subject separately.