Probabilistic failure risk assessment in ascending thoracic aortic aneurysms

This research is part of InSilicoHealth (www.insilicohealthproject.eu), an innovative Doctoral Network with the ambition to train a new generation of outstanding Doctoral Candidates that will become effective translators of the rapidly evolving digital technology to tackle existing and future challenges related with healthy ageing in Europe. The research focus of this doctoral network lies in three key domains: the brain, heart, and musculoskeletal systems. In the realm of digital technology, InSilicoHealth specifically focuses on virtual human twin technology to enhance our understanding of the age-related adaptive changes of the complex human body through predictive multi-scale simulations. The research methodology employs knowledge-driven models enhanced by advanced data-driven inference techniques to optimize the health potential of older individuals.
This project entails a joint doctoral degree between KU Leuven and Delft University of Technology. The research will be conducted in KU Leuven’s department of Mechanical Engineering division of Biomechancs (BMe) under the supervision of prof. dr. ir. Nele Famaey, and TU Delft’s department of BioMechanical Engineering under the supervision of dr. ir. Mathias Peirlinck. More information on both research groups can be found on https://www.mech.kuleuven.be/en/bme/research/soft-tissue-biomechanics and https://peirlincklab.com/
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We offer a full-time (100%) doctoral fellowship for 4 years, embedded in a multidisciplinary team of researchers, and within a highly dynamic and international European training network.
Website of the InSilicoHealth doctoral training network

Interested?

For more information please contact Prof. dr. ir. Nele Famaey, nele.famaey@kuleuven.be or Dr. ir. Lauranne Maes, lauranne.maes@kuleuven.be.

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