The quick and easy way for a new Member to create a List account, or for an existing Member to upload an up-to-date CV into your account.
Notes:
CVs can be uploaded with .doc, .docx or .pdf file extensions.
.rtf files cannot be accepted on the system. For new Members, the CV will be used to create an initial account which, once verified, will create a link to enable you to register and complete a full List account; you will not be able to apply for a job, or network, until you have done so.
For existing Members, provided the e-mail address you use above corresponds to that already recorded in your account, the new CV will be added to your account. Additionally uploading a CV will be taken as your agreement to our data management policy and terms.
Eligibility to Join: You must be a serving or former member, including the reserves, of the UK Armed Forces to be able to join The List. Exceptionally, we do permit non-UK forces people, who have been embedded within the UK Armed Forces, to join: if you fall into this latter category please Contact Us before registering.
Registration is free and easy and provides access to additional facilities within this site.
If you wish to advertise a job please register as an Advertiser through the Add a Vacancy tab on the website not here.
PLEASE NOTE: once you click "Sign Up" above our system will send an instantaneous verification e-mail to the address you have entered above.
To confirm registration you will need to click on the link in that e-mail otherwise you will not have completed registration. (The e-mail will come from: membership@thelistuk.com - please check your junk/spam folder if you do not immediately see the mail in your inbox.
Postdoctoral Research Associate in Image-based Vascular Modelling for AI and CFD in Digital Twin Assisted Surgery
Job Summary
Advertiser
Salary / Rate
Posted
University of Strathclyde
£37,694 - £46,049
10th February 2026
Location
Start Date
UK
Type
Job Sector
{}
Scientific
You will develop patient-specific vascular models from medical images to drive AI and CFD approaches for next-generation surgical planning and intervention. This post sits within a large, multidisciplinary EPSRC-funded Transformative Healthcare Technologies project “Real-time Digital Twin Assisted Surgery” (Ref: EP/X033686/1, £4M), bringing together expertise in medical imaging, computational modelling, artificial intelligence, surgery and biomedical engineering. In this role, you will lead the image-to-model framework, transforming clinical imaging data into high-fidelity 3D vascular geometries that underpin both data-driven (AI) and physics-based (CFD) digital twins. Your work will shape how personalised surgical strategies are simulated, optimised and ultimately translated into the operating theatre. You will work closely with clinicians, AI researchers, computational modellers and biofabrication experts, and will be encouraged to lead methodological development, publish in…
