UOB
Multimodal Learning for Human-Centered Healthcare: Motion Understanding and Medical Imaging
✓ Funded (Competition)
🎓 Artificial Intelligence
🎓 Computer Vision
🎓 Data Science
🎓 Machine Learning
deep learning
medical imaging
healthcare AI
human motion analysis
multimodal learning
PhD project developing multimodal AI systems for healthcare monitoring, motion analysis, and medical imaging diagnostics.
Project Description
This PhD project focuses on developing multimodal machine learning methods for healthcare applications by integrating diverse data sources such as images, videos, sensor data, and clinical information.
The research will address two key areas: human motion understanding and medical image analysis. It will involve developing AI models for pose estimation, action recognition, and mobility assessment, particularly for conditions such as Parkinson’s disease and stroke. Additionally, the project will explore multimodal approaches for interpretable and data-efficient medical imaging analysis using clinical data and expert annotations.
The work aims to improve patient monitoring, diagnosis, and decision-making in healthcare through robust and interpretable AI systems.
Entry Requirements
MSc in Computer Science, Applied Mathematics, Biomedical Engineering, or related field
• Strong background in machine learning/deep learning
• Programming skills (Python, PyTorch or TensorFlow)
• Experience in biomedical imaging or healthcare data (preferred)
• Strong background in machine learning/deep learning
• Programming skills (Python, PyTorch or TensorFlow)
• Experience in biomedical imaging or healthcare data (preferred)
How to Apply
Contact supervisor with CV to express interest.
Eligibility
UK/Home
EU
International
Supervisor Profile
DQ
Dr Qianhui Men
University of Bristol, School of Engineering Mathematics and Technology
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