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Featured bySwansea University
Overview
Scholarship type
Merit based
Number of scholarships to award
Multiple
Grant
Full tuition waiver + £18,622
Scholarship coverage
- tuition fee reduction
- other
Description
This project represents a new approach to map dynamical interactions in networks of human cardiac cells. Network dyssynchronisation is a fundamental event in the catastrophic breakdown of heart rhythm but they do not know the causative events that lead to the failure of cell-to-cell interactions. Moving beyond vague observational descriptions of network behaviours this project will implement a new system to precisely quantify time-resolved information on cell-to-cell interactions. Our approach involves the development of an innovative methodological framework that employs machine learning (ML) to define the intricate nature of intercellular interactions in such networks.
They will utilise large datasets and videos acquired from human cellular networks under a range of experimental conditions designed to stabilise or destabilise functional coupling between cells in the networks. The project will use our expertise in developing tailored algorithms for information extraction, pattern recognition and uncertainty estimation concerning the available clinical data. ML algorithms will enable new predictions and signal extrapolation from image datasets of cellular network behaviour.
Applicable programmes
Benefits
This scholarship covers the full cost of UK tuition fees and an annual stipend at UKRI rate (currently £18,622 for 2023/24).
Additional research expenses will also be available.
Eligibility
- Candidates must hold an undergraduate degree at 2.1 level in Computer Science, Mathematics or a closely related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).
- If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check their comparison entry requirements (see country specific qualifications).
- Please note that you may need to provide evidence of your English Language proficiency.
- Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.
Scholarship requirements
Disciplines
Computer Sciences
Locations
United Kingdom
Nationality
Any
Study experience required
Master
Age
Unknown
Application
Application deadline
01 May 2024
To apply, please complete your application online with the following information:
Course choice – please select Computer Science / PhD / Full-time / 3 Years / July (or October)
Start year – please select 2024
Funding (page 8) –
‘Are you funding your studies yourself?’ – please select No
‘Name of Individual or organisation providing funds for study’ – please enter ‘RS585 - Machine Learning’
*It is the responsibility of the applicant to list the above information accurately when applying, please note that applications received without the above information listed will not be considered for the scholarship award.
One application is required per individual Swansea University led research scholarship award; applications cannot be considered listing multiple Swansea University led research scholarship awards.