Computer Science Fully Funded Swansea University PhD Scholarship: Enhancing Cardiomyocyte Dynamic Network Analysis with Machine Learning (Ecidna-ML)

Updated: 26 days ago
Location: Swansea, WALES
Job Type: FullTime
Deadline: 01 May 2024

3 Apr 2024
Job Information
Organisation/Company

Swansea University
Department

Central
Research Field

Computer science » Other
Researcher Profile

First Stage Researcher (R1)
Country

United Kingdom
Application Deadline

1 May 2024 - 23:59 (Europe/London)
Type of Contract

Other
Job Status

Full-time
Hours Per Week

35
Offer Starting Date

1 Jul 2024
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Computer Science Fully Funded Swansea University PhD Scholarship: Enhancing Cardiomyocyte Dynamic Network Analysis with Machine Learning (Ecidna-ML)

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 we 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. We 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. This new framework will add new knowledge on the spatial and temporal nature of intercellular dyssynchronisation and yield unprecedented insights into cardiomyocyte network dynamics. The outputs of this work will lead to an improved understanding of the early events underpinning the functional decline of heart muscle and will ultimately inform better diagnosis and therapeutic interventions in heart disease. 


Requirements
Research Field
Computer science » Other
Education Level
Bachelor Degree or equivalent

Skills/Qualifications

 

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 our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency. 


Specific Requirements

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 . 


Additional Information
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 criteria

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 our comparison entry requirements. 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 . 


Selection process

Please see our website for more information.


Website for additional job details

https://www.swansea.ac.uk/postgraduate/scholarships/research/computer-science-s…

Work Location(s)
Number of offers available
1
Company/Institute
Swansea University
Country
United Kingdom
City
Swansea
Postal Code
SA2 8PP
Geofield


Where to apply
Website

https://www.swansea.ac.uk/postgraduate/scholarships/research/computer-science-s…

Contact
City

Swansea
Website

https://www.swansea.ac.uk/postgraduate/scholarships/research/computer-science-su-phd-enhancing-2023-rs585.php?utm_source=euraxess&utm_medium=scholarship&utm_campaign=postgraduate24&utm_content=pgr
Street

Singleton Park
Postal Code

SA28PP
E-Mail

[email protected]

STATUS: EXPIRED

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