Postdoc Multi-Scale Mechanobiological Cardiac Growth and Remodelling

Delft; Delft; On-site; EUR 42,000 - 54,000; Full time

Job summary

TU Delft seeks a postdoctoral researcher to advance multi-scale mechanobiological models of cardiac growth and remodeling within the VITAL project. You will develop, implement, and analyze bio-chemo-mechanical laws in finite element frameworks, linking tissue mechanics with systemic inputs and patient-specific simulations.

The role emphasizes rigorous mechanics, machine learning, and scientific software development, with collaboration across an international consortium and mentorship of students.

Qualifications

• PhD in a relevant field with a strong background in nonlinear mechanics.
• Proven ability to implement and analyze multi-scale cardiac mechanics models.
• Experience with computational modeling of growth and remodeling is preferred.

Responsibilities

• Develop bio-chemo-mechanical growth/remodeling laws for myocardial tissue.
• Implement laws in finite element cardiac mechanics frameworks.
• Couple tissue mechanics to systemic hemodynamics and neurohumoral inputs.
• Contribute to patient-specific or cohort-level virtual twin simulations.
• Develop calibration workflows, sensitivity analysis, and surrogate modeling.
• Create well-documented scientific software and publish results.

Skills

Python

Julia

C++

Fortran

Git

English (written/spoken)

Independent

Collaboration in multidisciplinary lab

Education

PhD in mechanical engineering or related

Tools

Abaqus

deal.II

FEniCS

JAX-FEM

Job description

Postdoc Multi-Scale Mechanobiological Cardiac Growth and Remodelling

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.

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.

TU Delft (Delft University of Technology)

Working at TU Delft means contributing to solutions that really make a difference.

For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow.

These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.

Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

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.
• 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. .