Job offer Bayesian inference of pulsatile flow through compliant boundaries

University of Cambridge, Newtown, Cambridge

Job offer Bayesian inference of pulsatile flow through compliant boundaries

Salary not available. View on company website.

University of Cambridge, Newtown, Cambridge

  • Full time
  • Temporary
  • Onsite working

Posted 1 week ago, 28 May | Get your application in now before you miss out!

Closing date: Closing date not specified

Job ref: 939c10c857774b169563615b5f9907d2

Location ref: Newtown, Cambridge

Full Job Description

Bachelor Degree or equivalent

Research Field
Mathematics » Applied mathematics

Education Level
Bachelor Degree or equivalent

Skills/Qualifications

Applicants should have (or expect to obtain by the start date) an excellent undergraduate or masters degree (or equivalent) in fluid mechanics, applied mathematics, scientific computing, or related fields.

The applicant will have some experience with programming, e.g. with python, C++, Matlab. The role holder will have a strong background in fluid mechanics, numerical methods, PDEs, Finite Element Methods, or functional analysis.

Languages
ENGLISH

Level
Good

Research Field
Engineering » Mechanical engineering

Years of Research Experience
1 - 4

Flow-MRI (magnetic resonance imaging) is a non-invasive imaging method that visualizes fluid flows in the body in 4D (3 spatial and 1 time dimension) without using ionizing radiation. It holds great promise for comprehensive characterization of blood velocity, particularly in the heart and major blood vessels, but is currently hindered by low signal-to-noise ratio (SNR) and low spatial resolution.

The Principal Investigator's research group has developed a method that assimilates sparse and noisy Flow-MRI data directly into a computational fluid dynamics (CFD) simulation. This method uses Bayesian inference, which is also known as probabilistic machine learning. The Bayesian inference code wraps around a differentiable Finite Element Method code, which combines adjoint methods with Laplace's method to assimilate data and estimate uncertainties., Applicants must be in their first 4 years of their research career and have not yet been awarded a doctoral degree. The 4 years are counted from the date a degree was obtained which formally entitles one to embark on a doctorate.

According to the international mobility rules of the MSCA-DN program, the candidates must not have spent more than 12 months in the hosting country (UK), during the 36 months preceding the starting of the PhD.
Selection process

Direct job link

https://www.jobs24.co.uk/job/job-offer-bayesian-inference-of-pulsatile-flow-126901355