PhD Position Physics-Based and Experimental Data-Driven Cardiovascular Disease Modeling

Job description

Cardiovascular disease remains a leading cause of morbidity and mortality worldwide. The advent of in silico models has provided unprecedented opportunities for understanding, diagnosing, and treating these conditions through patient-specific simulations. However, the current deterministic nature of these models presents a significant barrier to their widespread adoption by industry and clinicians. Deterministic models often fail to capture the inherent variability and uncertainties present in biological systems, which can lead to misinterpretations and suboptimal clinical decisions.

In this project, you will address these challenges by developing robust methods for uncertainty quantification and propagation within virtual human twin models of cardiovascular disease. More specifically, you will develop a systematic framework to quantify the impact of inherent inter-sample and -subject variability associated with experimental tissue tests, the intrinsic uncertainty of in vitro and in vivo imaging techniques, and the effect of noisy experimental and clinical measurements on computational models of the diseased heart and aorta.

This project entails a joint doctoral degree between Delft University of Technology and KU Leuven. The research will be conducted in TU Delft’s department of BioMechanical Engineering under the supervision of dr. ir. Mathias Peirlinck, and KU Leuven’s department of Mechanical Engineering division of Biomechancs (BMe) under the supervision of prof. dr. ir. Nele Famaey. More information on both research groups can be found on and .

This research is part of InSilicoHealth (), 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 DN 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.

Host institution: TU Delft, The Netherlands. Secondments planned at KU Leuven and with industrial partner.

Supervisory team: Dr. Mathias Peirlinck (PhD main supervisor, TUDelft), Prof. Nele Famaey (PhD co-supervisor, KU Leuven)

Enrolment in Doctoral School: Enrolled in the Graduate School of the TU Delft Faculty Mechanical, Maritime and Materials Engineering (TU Delft) and the Arenberg Doctoral School for Science, Engineering & Technology (KU Leuven).

Keywords:

soft tissue biomechanics, computational mechanics, uncertainty quantification, sensitivity analysis, parameter identification, inverse problems, Bayesian inference, Gaussian Processes, in silico medicine, in vitro tissue characterization, scientific machine learning, numerical analysis, cardiovascular digital twins

Requirements

• You have demonstrable experience with nonlinear continuum mechanics, finite element analysis, cardiovascular modeling, computational soft tissue biomechanics and cardiovascular (patho)physiology.
• Affinity with scientific machine learning, Bayesian inference, data-driven modeling, and/or numerical analysis of PDEs and ODEs on complex domains is highly appreciated.
• You have an excellent master’s degree (or an equivalent university degree) in Biomedical Engineering, Mechanical Engineering, Aerospace Engineering, Computational Physics, Applied Mathematics or a related field.
• You are ambitious, well organized, a team player, and have excellent communication skills.
• You can work independently, are a quick learner, and have a critical research-oriented mindset.
• You are a pro-active and motivated person, eager to participate in network-wide training events, international mobility, and public dissemination activities.
• You can effectively communicate scientific ideas, and foster collaborations in a highly multidisciplinary team.
• You have excellent spoken and written English* language skills (minimum C1 level).

Please highlight your specific skills and relevant prior experiences for this position explicitly in your motivation letter. Motivation letters that do not address any of these requirements will not be considered.

*Doing a PhD at TU Delft requires excellent English proficiency to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details, please check the Graduate Schools Admission Requirements.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the .

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2872 per month in the first year to € 3670 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a  for partners and they organise events to expand your (social) network.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core  and we actively  to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact

Faculty Mechanical Engineering

From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.

ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research, inspiring education and (inter)national cooperation.

Click  to go to the website of the Faculty of Mechanical Engineering. Do you want to experience working at our faculty? These  will introduce you to some of our researchers and their work.

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