VAC-2025-66 - Computational Cardiovascular Modelling (FPI 2024)

Functions to be developed: A doctoral thesis in the framework of the research project entitled INNOVECMO: Estudios Computacionales, Experimentales y de Prototipado para el Desarrollo de Sistemas Innovadores de Oxigenación Extracorpórea Sin Válvulas, with reference Project PID OB-C21 funded by MCIN/AEI /9/ and by FEDER, EU. Principal investigators: Prof. Eduardo Soudah Pirieto y Joaquin Alberto Hernandez Ortega. The Biomedical Engineering Group is seeking a motivated and enthusiastic PhD candidate to join our team. The research will focus on the numerical modelling and/or experimental study of an innovative cardiovascular device. The aim is to design and improve device performance using computational models (e.g., Finite Element Analysis or related methods). These models are increasingly important as decision-support tools in the preoperative phase. However, despite their high predictive power, they often demand substantial computational resources and time, which limits their routine clinical use. This project will address this challenge by developing fast computational models capable of accurately predicting the interaction between devices and the human body. The candidate will contribute to the creation of next-generation, clinically oriented simulations for cardiovascular devices, combining: Computational Biomechanics (CB): development of tools to capture the physics behind cardiovascular device. Physics-informed Machine Learning (ML): advanced AI methods designed to accelerate simulations while preserving the validity of underlying physical laws. The ultimate goal is to deliver fast, accurate, and efficient tools to predict cardiovascular device behaviour under different physiological conditions. This will enable faster testing, more reliable surgical planning, and improved patient outcomes. The research will be validated through specific clinical use cases, in close collaboration with experimental and clinical partners. The candidate participates in a coordinate project lead by CIMNE in collaboration with Universidad of Valladolid. If you are passionate about biomechanics, numerical methods, and AI in biomedical engineering, this is an exciting opportunity to engage in cutting-edge research with real clinical impact. Additional information about the project is available at: CIMNE RTD Project: The candidate will join the research group of: Bio-Medical Engineering This contract is financed by the announcement of Proyectos de Generación de Conocimiento 2024 of the Ministerio de Ciencia, Innovación y universidades: Proyectos de Generación de conocimiento 2024| Agencia Estatal de Investigación () We offer: Opportunity to join a dynamic, young research group with an interdisciplinary focus and strong track record of the topic of this research line. Clinical-oriented research with direct impact on patient care and clinical practice. Extensive collaboration opportunities with hospitals, clinical practitioners, and leading international research groups, enhancing the translational potential of research outcomes and promoting international networking. Development and dissemination of open-access computational tools and codes, including contributions to in-house platforms, such as, KRATOS Multiphysics, amongst others. Required skills: The candidate must have a Master's degree (or equivalent) in Bioengineering, Aeronautical, Civil, or Mechanical Engineering, applied sciences or mathematics; and to be in disposition to be enrolled in a PhD programme in the moment of the contract’s formalization. Good written and oral communication skills in English. Advanced programming skills (such as Python, Matlab, …). Hard-working and enthusiastic attitude towards research and innovation. Team work spirit. Knowledge on the Computational Cardiovascular dynamics (not mandatory) Qualification system: The requisites and merits will be evaluated with a maximum note of 100 points (Minimum required of 90 points). The evaluation process must comply with the following criteria : Academic and/or scientific-technical background of the candidate (up to 20 points). Scientific-technical contributions (up to 15 points). The candidate's academic record and other curricular merits will be evaluated, as well as their suitability to the tasks to be performed based on the candidate's training and professional experience. Mobility and internationalization (up to 5 points). The relevance and impact of the candidate's stays in national and international centers and/or in the industrial sector on his/her research career will be assessed, taking into