Research Associate in Multiphysics-Informed Machine Learning for Cardiovascular Biomechanics

5 days ago


Oxford, United States The University of Manchester Full time

We are seeking a highly skilled Research Associate to join our multidisciplinary team at The University of Manchester. As a Research Associate, you will play a key role in developing high-fidelity models of cardiovascular fluid dynamics and device-flow/device-tissue interactions through multi-physics and physiological modeling.

Key Responsibilities:

  • Develop and apply computational models of cardiovascular mechanics and prosthetic valves using computational solid mechanics and fluid dynamics.
  • Collaborate with our team to leverage clinical and experimental data, first-principle physics-based simulations, scientific machine learning approaches, data assimilation, and uncertainty quantification techniques.
  • Apply these techniques to large real-world multimodal datasets, clinical trials datasets, and population imaging studies.
  • Contribute to the development of accelerated methods for solving partial differential equations and scientific machine learning (physics-informed machine learning).

Requirements:

  • PhD in computational cardiovascular mechanics and prosthetic valves or related fields.
  • Expertise in computational solid mechanics or computational fluid mechanics.
  • Experience in working with multiphysics and multiscale models.
  • Developing publication profile.

What We Offer:

  • Fantastic market-leading pension scheme.
  • Excellent employee health and wellbeing services.
  • Exceptional starting annual leave entitlement.
  • Additional paid closure over the Christmas period.
  • Local and national discounts at a range of major retailers.

Language: English (en-US)



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