PhD in Credible hybrid AI-mechanistic models for clinical decision-making: unveiling the untapped potential of sensitivity analysis methods

Introduction

• Are you eager to apply mathematics to improve medical decision support?
• Are you passionate about joining a multidisciplinary team working to revolutionise personalized medicine?
• Are you excited to develop trustworthy, explainable, hybrid physics-AI models for cardiovascular biomechanics?

Job Description

At the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), we offer a fully funded 4-year PhD position within the project HY-Credibility - Credible hybrid AI–mechanistic models for clinical decision-making: unveiling the untapped potential of sensitivity analysis methods. You will be embedded in the Cardiovascular Biomechanics group led by Prof. Huberts and co-supervised by dr. Jemima Tabeart of the Computational Science group, Centre for Analysis, Scientific Computing and Applications (Department of Mathematics & Computer Science).

Your challenge: Extracorporeal membrane oxygenation (ECMO) is a life-saving therapy, but deciding when and how to safely wean patients from cardio-respiratory support remains a major clinical challenge. In this project, you will develop credible hybrid digital twins that combine first-principles cardiovascular pathophysiology with data-driven AI. A key innovation is the use of sensitivity analysis (SA) and uncertainty quantification (UQ) to make these models transparent, testable, and trustworthy for clinical decision-making. You will help answer: how can we provide uncertainty-aware, explainable advice for safe ECMO weaning?

Your role: You will design and develop hybrid models that combine fast physiological signals with slower patient-specific dynamics, and build an SA/UQ toolbox for high-dimensional hybrid systems. You will work with unique datasets generated from an advanced ECMO mock loop, perform simulation and data assimilation studies, and evaluate model credibility, robustness, and generalizability. Your work will be closely connected to clinical practice and includes collaboration with clinicians and interdisciplinary experts. You will publish your results, contribute to open datasets and tools, and help supervise BSc/MSc students.

Your impact: This project contributes directly to safer, more personalized care for critically ill patients. By enabling uncertainty-aware and explainable decision support for ECMO weaning, your work will reduce trial-and-error decisions and improve patient outcomes. More broadly, you will help establish trustworthy hybrid AI methodologies for safety-critical applications in healthcare and beyond.

Your environment: You will work in an interdisciplinary and supportive team at the interface of biomedical engineering, applied mathematics, and AI. TU/e offers a collaborative and inclusive research culture, with strong links to clinical partners and leading expertise in computational modelling, digital twins, and uncertainty quantification.

Job Requirements

We are looking for a candidate who meets the following requirements:

• You are creative and ambitious, with a proactive, persistent, and results-driven mindset.
• You have a strong background in mathematics, developed during your MSc in Applied Mathematics, Biomedical Engineering, Mechanical Engineering, Physics, or a related field.
• You are comfortable with in-depth mathematical reasoning.
• You have a research-oriented attitude and enjoy tackling complex, open-ended problems.
• You communicate clearly and effectively, and contribute positively to a collaborative research environment.
• You are able to work in interdisciplinary teams and are interested in collaborating with clinical and/or industrial partners.
• You are motivated to develop your teaching skills and to supervise and coach students.
• You have a good command of English, both written and spoken (minimum level C1).

It would also be beneficial for candidates to have

• Theoretical and/or applied knowledge of biomechanical modelling (in silico and/or in vitro)
• Prior experience with AI or hybrid modelling approaches.

Conditions of Employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you: 

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. 
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881). This salary is in accordance with the MSCA Call 2024 regulations for Doctoral Researchers and will be paid from the relevant monthly gross allowances (gross living allowance € 4.010 per month; mobility allowance € 710 per month; family allowance € 660 per month, only if applicable).   
• A year-end bonus of 8.3% and annual vacation pay of 8%. 
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process. 
• An excellent technical infrastructure, on-campus children's day care and sports facilities.  
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate.
• An allowance for commuting, working from home and internet costs. 
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates. 

On our website you can discover even more information about our conditions of employment. Build on your career at TU/e!

About us

We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

Our university is located in Brainport Eindhoven — a world‑leading tech region with more than 7,000 high‑tech companies and strong R&D activity. Known for breakthroughs in AI, photonics, semiconductors and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here.

The Department of Biomedical Engineering offers top-level education and research in one of the most relevant and exciting scientific disciplines of the 21st century: engineering health. In combining engineering and life sciences, through challenge-based learning and a multidisciplinary approach in collaboration with hospitals, industry and others, the department addresses the great challenges of the future, striving to improve healthcare and society as a whole.

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Prof. Wouter Huberts ([email protected]) or Dr. Jemima Tabeart ([email protected]).

Visit our website for more information about the application process. You can also contact Sascha Sanchez van Oort, HR Advisor, [email protected].

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

• a motivation letter, including the topic of your MSc thesis project.
• a list of BSc and MSc courses and grades. a curriculum vitae (including contact details of at least three references). Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.
• a list of BSc and MSc courses and grades. 

Ensure that you submit all the requested application documents. We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post. 
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.