项目介绍

2026年5月2日

Are you a motivated recent graduate with a master’s degree and with a strong interest in data science, biomechanics, and biomedical research? Do you want to work at the forefront of AI-driven healthcare innovation?
Join the ERC-funded OA-CONNECT project (Pi Ilse Jonkers), where we tackle a fundamental and unresolved question: why does mechanical loading—normally essential for cartilage and chondrocyte health—become harmful in osteoarthritis (OA)?
Project context
OA-CONNECT is a cutting-edge, interdisciplinary research program that connects joint-level biomechanics to cellular processes through a multiscale approach. By integrating in vitro, in silico, and in vivo methodologies, we aim to map the full pathway from mechanical stimulus to cellular response, and uncover the mechanisms driving cartilage degeneration.
This PhD project contributes to a key ambition of OA-CONNECT: developing scalable, data-driven tools to predict osteoarthritis progression and personalize treatment strategies. By combining biomechanics, multiscale computational modeling, artificial intelligence, and clinical data, we aim to move toward predictive and personalized care for knee osteoarthritis patients.

Unit website

Project

Your research focus

You will focus on the patient-oriented (in vivo) component of the project, developing AI-enhanced, patient-specific predictive models of cartilage degeneration.

Specifically, you will contribute to the development of an innovative framework that integrates:

• Real-world biomechanical data (wearables, video analysis)
• Clinical data (medical imaging and biomarkers)
• Multiscale computational models

to predict cartilage degeneration and treatment response in knee osteoarthritis.

Your role

As a PhD researcher within OA-CONNECT, you will:

• Process and analyze real-world biomechanical data from wearables and video recordings to quantify joint loading in daily life
• Implement and extend musculoskeletal and cartilage loading models using these data
• Develop, train, and evaluate AI models (e.g., deep learning) to extract patient-specific parameters from clinical datasets
• Build and test probabilistic models to predict cartilage degeneration and disease progression
• Integrate biomechanical, imaging, and clinical datasets into a unified modeling framework
• Validate model predictions using data from a prospective clinical cohort of knee osteoarthritis patients
• Translate modeling results into clinically meaningful insights on disease progression and treatment response
• Develop reproducible analysis pipelines and contribute to open and robust research practices
• Collaborate closely with a multidisciplinary team of engineers, clinicians, and data scientists
• Disseminate your work through high-impact publications, conferences, and outreach

You will work under the supervision of Ilse Jonkers, with co-supervision by Maarten De Vos and Lennart Scheys at KU Leuven.

Profile

Your profile

We are looking for a highly motivated candidate who is eager to work at the intersection of AI, biomechanics, and clinical research:

• A master’s degree in engineering sciences or biomedical engineering, with a strong foundation in artificial intelligence or data science
• Strong interest in machine learning (e.g., deep learning, convolutional neural networks) and biomechanical modeling
• Programming experience (e.g., Python, MATLAB, or similar)
• Strong analytical and problem-solving skills, with a critical scientific mindset
• Interest in interdisciplinary research bridging engineering, data science, and healthcare
• Ability to work independently, combined with a collaborative and proactive attitude
• Excellent communication skills in English

Experience with musculoskeletal modeling (e.g., OpenSim), multiscale modeling, or machine learning applications in healthcare is a strong asset.

Offer

• A fully funded 4-year PhD position within a prestigious ERC Advanced Grant project. At the end of the first year, a formal evaluation will take place, which is decisive for the continuation of funding for the remaining three years. Candidates are expected to apply for a personal PhD fellowship (FWO) during their first year, with institutional support.
• A high-impact research topic at the forefront of AI-driven, personalized healthcare
• Access to unique multimodal datasets (wearables, clinical cohorts, imaging, biomarkers)
• A state-of-the-art research environment at KU Leuven, with strong links to clinical and engineering domains
• Close collaboration with leading experts in biomechanics, AI, and clinical research
• Strong support for your scientific and professional development, including mentoring, international conference participation, and networking opportunities

Interested?

For more information please contact Prof. dr. Ilse Jonkers, mail: ilse.jonkers@kuleuven.be.You can apply for this job no later than June 01, 2026 via the online application tool