PhD Researcher in AI-Driven Personalised Fracture Risk Prediction
Develop AI models to predict personalised hip fracture risk from medical imaging and longitudinal data in Singapore.
Best for:Best for AI/ML researchers with expertise in medical image processing, deep learning (PyTorch), and a strong quantitative background in computer science, engineering, or related fields.
Overview
This PhD position at the Singapore-ETH Centre (SEC) focuses on advancing AI-driven medical imaging to predict personalised hip fracture risk from bone-density and CT scans. The project aims to replace computationally expensive biomechanical simulations with data-driven models that can process routine imaging in seconds. The successful candidate will work on developing deep-learning models for medical images, extending them to longitudinal data to forecast fracture risk trajectories. The role involves collaboration with a multidisciplinary team, co-supervision of MSc/BSc students, and validation of models against biomechanical simulations and real-world outcomes. The position is based in Singapore and offers a 4-year contract with funding provided by ETH Zurich.
What you'll do
- Develop AI/deep-learning models to predict personalised hip fracture risk from bone-density and CT scans.
- Extend image-based models to longitudinal data to forecast bone-ageing trajectories and future fracture risk from repeat scans.
- Validate model predictions against biomechanical simulations and real-world fracture outcomes across diverse cohorts.
- Collaborate with a multidisciplinary team of researchers and co-supervise MSc and BSc students.
- Work on generative and image-assessment approaches to improve predictive accuracy and clinical applicability.
Requirements
Degree required: Master's degree (MSc) in computer science, engineering, mathematics, physics, or a related quantitative discipline
Degree offered: PhD
Language: English; proficiency in written and spoken English required
Instruction: English
- Strong background in machine learning and deep learning
- Proficient Python programming skills
- Prior experience training and evaluating neural network models (e.g., using PyTorch)
- Familiarity with medical image processing
- Experience with software engineering practices, including version control and collaborative development workflows
- Proficiency in written and spoken English
- No specific nationality or residency restrictions mentioned
- No age limits or prior experience caps mentioned
Funding & terms
How to apply
Applicants must submit their application through the Singapore-ETH Centre’s online application portal. Required documents include a cover letter with a motivation statement, a CV with contact details of two references, and university transcripts as PDFs. Applications via email or postal services will not be considered.
- Cover letter with motivation statement
- CV including names and contact information of 2 references
- University transcripts as PDFs
Contact
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