Challenge: Predict long-term cardiac growth and remodeling in cardiovascular disease.
Change: Develop multi-scale mechanobiological models for virtual human twins.
Impact: Advance patient-specific modeling of disease progression and treatment response.

Job description

Cardiovascular disorders often progress over months to years through complex interactions between myocardial mechanics, tissue adaptation, systemic hemodynamic and biochemical regulation. To understand and predict these processes, virtual human twins need to move beyond acute simulations of cardiac function and incorporate long-term growth and remodeling of the heart.

At Delft University of Technology, we are looking for a postdoctoral researcher to develop next-generation computational models of cardiac growth and remodeling within VITAL: Virtual Twins as Tools for Personalized Clinical Care, a European Union-funded Horizon Europe project. VITAL develops clinically relevant virtual human twin technology for personalized cardiovascular care. Within the consortium, TU Delft contributes expertise in cardiac mechanics, soft tissue modeling, growth and remodeling, machine learning, and uncertainty-aware model personalization.

As a postdoctoral researcher, you will develop, implement, and analyze cardiac growth and remodeling models in finite element frameworks for cardiac mechanics. Your work will focus on bio-chemo-mechanical and constituent-specific remodeling laws that describe chronic changes in myocardial structure and function. You will couple tissue-level cardiac mechanics to systemic hemodynamic and neurohumoral inputs within the VITAL consortium and contribute to patient-specific or cohort-level virtual human twin simulations.

You will also contribute to patient-specific model calibration workflows, including sensitivity analysis, uncertainty-aware parameter estimation, surrogate modeling, and reduced-order modeling where relevant. The scientific emphasis is mechanics-first: we are looking for someone with strong foundations in nonlinear mechanics, finite element modeling, and multi-scale biomechanics who is motivated to work at the interface of cardiac mechanobiology, machine learning, and scientific software development.

You will be part of the lab of dr. ir. M. Peirlinck in the Department of BioMechanical Engineering at TU Delft. Our group combines nonlinear mechanics, computational modeling, experimental and clinical data, and machine learning to understand and predict the behavior of cardiovascular tissues and organs across scales. You will work closely with PhD students, MSc students, and international VITAL partners. This is a full-time, on-site postdoc position based at TU Delft in Delft. The initial appointment is for one year, with the possibility of extension, subject to progress and project conditions.

In this role, you will:

• Develop bio-chemo-mechanical cardiac growth and remodeling laws for chronic changes in myocardial structure and function
• Implement these laws in finite element cardiac mechanics frameworks
• Couple tissue-level cardiac mechanics to systemic hemodynamic and neurohumoral inputs within the VITAL consortium
• Contribute to patient-specific and cohort-level virtual human twin simulations
• Contribute to patient-specific calibration, uncertainty-aware parameter estimation, and model reduction workflows
• Develop robust, reusable, and well-documented scientific software in collaboration with other researchers
• Publish high-quality journal articles and present your work at international conferences
• Contribute to the mentorship/support of PhD and MSc students and participate in the scientific life of the lab and consortium

This position is an opportunity to work at the interface of rigorous computational mechanics, mechanobiology, machine learning, and translational cardiovascular modeling. We are looking for a motivated researcher who wants to develop scientific ideas while contributing to a larger international team effort.

Job requirements

You are an ambitious, independent and collaborative researcher with a strong background in computational mechanics and a clear interest in cardiovascular growth and remodeling. We are looking for a mechanics-first profile: rigorous training in nonlinear mechanics, finite element modeling, and multi-scale biomechanics is most important, while experience applying these methods to cardiovascular problems is a plus.

Required qualifications

• A PhD in mechanical engineering, applied mathematics, computational science, biophysics, biomedical engineering, or a closely related field.
• Strong background in nonlinear continuum mechanics, tensor algebra, and finite element modeling.
• Experience with computational solid mechanics, computational soft tissue mechanics, or a closely related mechanics field.
• Well-developed coding expertise in Python, Julia, C++, Fortran, or a similar scientific computing language.
• Experience with Git and collaborative scientific software development.
• Excellent analytical and problem-solving skills, and excellent written and spoken English.
• Ability to work independently while contributing to a multidisciplinary consortium.

Nice-to-haves

• Knowledge of cardiovascular biomechanics, growth and remodeling theory, mechanobiology, active cardiac mechanics, or adaptive soft tissue modeling.
• Experience developing or extending finite element software or research codes.
• Practical experience with Abaqus, deal.II, FEniCS, JAX-FEM, or comparable finite element frameworks.
• Experience with uncertainty quantification, Bayesian inference, inverse modelling, parameter estimation, or model calibration.
• Experience with high-performance computing, surrogate modelling, reduced-order modelling, or machine-learning-assisted computational mechanics.
• Experience with patient-specific modelling, or virtual cohort simulations.
• Interest in mentoring students, scientific writing, and future proposal development.

To help us assess your fit, please use your motivation letter to explain how your background connects to the required qualifications and nice-to-haves. We encourage candidates to apply even if they do not meet every nice-to-have, provided they have a strong foundation in computational mechanics and scientific software development.

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

Conditions of employment

• Duration of contract is 1 year Temporarily with a posibility for extension
• A job of 38 hours per week.
• Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Flexible working week.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave
• Attention for working healthy and energetically with the vitality program.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands. .

Additional information

If you would like more information about this vacancy or the selection procedure, please contact recruitment-me@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply no later than 15 September 2026 via the application button and upload the following documents:

• Motivation letter or research statement explaining your interest in the position and how your background connects to the project.
• Detailed CV, including a list of publications.
• Copy of your PhD degree and transcript.
• At least two relevant publications. Additional publications are welcome.
• If the applicants are selected for an interview, they will be asked to provide names and contact information of at least three relevant references, with their consent.

Recruitment interviews may start before the application deadline, so we encourage interested candidates to apply as soon as possible.

Please note:

• #EUfunded This is an EU funded project, named VITAL - Virtual Twins as Tools for Personalised Clinical Care, with project number 101136728, within program Horizon Europe (HORIZON)
• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.