The Singapore-ETH Centre was established in 2010 by ETH Zurich - The Swiss Federal Institute of Technology and Singapore’s National Research Foundation (NRF), as part of the NRF’s CREATE campus. As ETH Zurich's only research centre outside of Switzerland, the centre has strengthened the research capacity of ETH Zurich to develop sustainable solutions to global challenges in Switzerland, Singapore and the surrounding regions.

Set in Asia, in a rapidly urbanising region, the Singapore-ETH Centre aims to provide practical solutions to some of the most pressing challenges on urban sustainability, resilience and health through its programmes: Future Cities Lab Global (FCL Global) and Future Health Technologies (FHT).

The centre serves as an intellectual hub for research, bringing together principal investigators and researchers from diverse disciplines and backgrounds. To promote the exchange of ideas and expertise, our researchers actively collaborate with universities and research institutes and engage with industry and government agencies to translate knowledge to practical solutions to real-world problems.

Micro-Multiphysics Agent-Based Modelling for Simulation of Patient-Specific Bone Remodelling

Fragility fractures are among the most serious consequences of impaired skeletal health in older adults and often lead to reduced mobility, loss of independence, and long-term disability. Although current standards of care provide important tools for assessing skeletal health and fracture risk, they do not fully capture how individual differences in bone remodelling, inflammation, mechanical loading, and biological tissue response influence fracture progression over time. Osteoporosis and related age-associated bone disorders are highly heterogeneous, with patients differing in bone formation capacity, osteoclast activity, inflammatory status, mineralisation dynamics, and capacity for mechanoadaptation. Computational models that integrate these biological and clinical differences could support more personalised strategies for fracture prevention and musculoskeletal care.

Building on the dynamic bone organoid culture platform developed in the Laboratory for Bone Biomechanics at ETH Zurich, this project aims to develop micro-multiphysics agent-based models (micro-MPA) that link patient-derived organoid readouts with clinical and imaging data. The doctoral researcher will develop computational workflows to simulate bone remodelling processes, mechanical-cytokine microenvironments, cellular dynamics, and patient-specific fracture risk trajectories. Biological outputs from patient-derived 3D bone organoids, including mineralisation dynamics, osteoclast activity, immune-bone interactions, inflammatory profiles, and mechanical response, will be translated into model parameters and integrated with relevant clinical datasets.

The resulting modelling framework will support the prediction of patient-specific bone remodelling trajectories and fracture risk under different biological and mechanical conditions, contributing to data-driven and human-relevant approaches for precision fracture prevention.

The PhD candidate will interact closely with engineers, clinicians, biologists, computational researchers, to generate a micro-MPA modelling framework supporting prediction of patient-specific bone remodelling trajectories and fracture risk.

Some key components in the work are:

• Development of micro-MPA modelling workflows for patient-specific bone remodelling and fracture risk prediction.
• Integration of biological readouts from patient-derived 3D bone organoids with clinical, imaging, and computational datasets.
• Simulation of bone remodelling processes, mechanical-cytokine microenvironments, cellular dynamics, and fracture risk trajectories.
• Development and validation of predictive modelling frameworks to support precision fracture prevention and personalised musculoskeletal care.

Applicants should hold an MSc degree in biomedical engineering, computational biology, computer science, applied mathematics, physics, mechanical engineering, or a related discipline. After successful completion of studies, the PhD degree will be awarded by ETH Zurich.

Candidates should have experience in computational modelling, numerical simulation, or data-driven modelling. Strong programming skills in Python or a related scientific programming language are required. Experience with agent-based modelling, multiphysics modelling, mechanobiology modelling, or tissue remodelling simulations would be advantageous.

Experience in medical imaging, computed tomography, image analysis, or morphometric analysis. Experience with machine learning, statistical modelling, parameter estimation, model calibration, sensitivity analysis, or model validation would be considered a strong advantage. Familiarity with bone biology, osteoporosis, skeletal mechanobiology, or organoid-derived biological datasets would be an additional asset.

Candidates should have excellent written and spoken English communication skills and be able to work on complex research topics with increasing independence. They should be motivated to work at the interface of computational modelling, skeletal biology, and precision musculoskeletal medicine. Familiarity with a cross-cultural and interdisciplinary research environment would be advantageous.

• Accredited with 5 Tripartite Standards by Tripartite Alliance for Fair & Progressive Employment Practices (TAFEP) Singapore. 
• A diverse workplace with 32 nationalities, offering ample opportunities for mutual learning. 
• Positive and inclusive working environment. 
• 25 days of annual leave for fixed-term contracts. 
• 1 day of Birthday Leave. 
• Annual dental benefits. 
• Committed to being a supportive employer as you prioritize your physical and mental wellness. 
• Comprehensive healthcare insurance coverage. 
• Flexible hybrid work arrangement (up to 2 days per week from home). 
• Abundant networking opportunities across various disciplines. 
• Accredited with NS mark certification. 

We look forward to receiving your online application with the following documents:

• A cover letter with a specific statement of your motivation for the project.
• Your CV including the name and contact information of 2 academic references.
• A copy of your university transcripts as PDFs.

Further information about The Singapore-ETH Centre can be found on our website. Questions regarding the position should be directed to Prof. Dr. Ralph Müller (ETH Zurich), [email protected]

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.