miquel.aguirre's blog
Postdoc position at CIMNE Barcelona in data-driven modelling for endovascular thrombectomy
We are looking for a postdoctoral researcher to work on the project MECA-ICTUS, a 3-year project funded under the Generación de Conocimiento 2022 call of Agencia Estatal de Investigación. In MECA-ICTUS we will pursue the development of computational mechanics and machine learning tools for predicting the success of endovascular thrombectomy, an urgent intervention for the removal of thrombi in Acute Ischemic Stroke Patients.
EndoBeams.jl: A Julia finite element package for beam-to-surface contact problems in cardiovascular mechanics
Please take a look at the paper of our PhD student Beatrice Bisighini in Advances in Engineering Software: "EndoBeams.jl: A Julia finite element package for beam-to-surface contact problems in cardiovascular mechanics". We propose an efficient framework for modelling beam-to-surface contact, specifically designed to model endovascular devices.
You can find the paper (open-access) here: https://www.sciencedirect.com/science/article/pii/S0965997822000849
PhD position Computational Modeling of blood flow and position to asses measurements of non-invasive devices- CEA - Mines Saint Étienne (France)
The LS2P laboratory (from its French name, Laboratoire des Systèmes Portés par la Personne ) develops non-invasive devices for measuring physiological parameters such as heart rate, oxygen saturation or blood pressure. A strong integration is a key factor from the design stage of the sensors. This allows them to be integrated into bracelets, patches or headbands to make them compatible with their daily use.
1 PhD position in Real time brain-perfusion simulation for Acute Ischemic Stroke using machine learning-based reduced order modelling
Objective: the objective of this doctoral position is to develop a real-time model of brain perfusion, by coupling a 1D-FSI model of blood flow with a 3D brain model of brain perfusion. Acceleration of the computation will be carried out using machine learning based reduced order modelling, leveraging from current work carried out at by the supervisors at CIS. Once available, the model will be coupled with additional models to provide a decision support tool for Acute Ischemic Stroke treatment.