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MRC AIM Doctoral Training Partnership

University of Nottingham - Mathematical Sciences

Location: Nottingham
Salary: Competitive Funding
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 8th December 2023
Closes: 12th January 2024
Job Ref: SCI247

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/.

The deadline for submitting applications is 12.00 am GMT, Friday, 12 January 2024. Interviews will take place during the week commencing 26 February and will be held via Zoom.  

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.

Full details can be found on the MRC website.

School of Mathematical Sciences

Project Title: Enhancing precision-cut lung-slice models with computational modelling and machine learning to understand mechanobiology in airway remodelling

Supervisors: Bindi Brook, bindi.brook@nottingham.ac.uk,

Amanda Tatler (UoN), Jinming Duan (UoB), Ian Sayers (UoN)

One of the key characteristics of asthma is the irreversible structural changes that occur in the airway wall, termed airway remodelling. This typically consists of increased amounts of airway smooth muscle and increased extracellular matrix among other changes. Recent evidence suggests that forces transmitted by contracting smooth muscle cells to airway tissue can activate growth factors that cause airway remodelling in asthmatics, worsening the condition. The link between tissue mechanics and biology in vivo is not well understood but is key to developing a complete understanding of airway remodelling. In this project we will bring together an experimental ex vivo model called precision-cut lung-slice (PCLS; in which cells maintain their contractile ability in their native environment) with histological staining (to identify different cell types and proteins), machine learning to enable automatic detection of airway constituents from stained PCLS, spatial transcriptomics and predictive mathematical models to predict sites of growth factor activation within the airway wall. You will join a multidisciplinary team that values collaboration and team working. You will have the opportunity to develop both cutting-edge wet-lab skills working with animal and human PCLS as well as computational quantitative skills in developing predictive mathematical models and machine learning approaches.

 

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