Postdoctoral Researcher in Computer Vision and Multimodal AI for the Early Detection of Parkinson’s
Core
Develop computer vision and multimodal AI tools for the early detection and monitoring of Parkinson's disease by analyzing video, speech, and sensor data.
Role type
Postdoctoral Researcher (Computer Vision & Multimodal AI)
Builds
Digital motor assessment platform (bradyMX) for patient stratification and clinical trial support
Domain
Neurology / Computer Vision / Multimodal AI
Deliverable
production ML models
Required skills
Computer vision, machine learning, deep learning, Python, PyTorch/TensorFlow/JAX, human pose estimation, motion tracking, temporal modelling, multimodal learning
Preferred skills
Self-supervised learning, domain adaptation, high-performance computing, containerized workflows
Technologies
PyTorch, TensorFlow, JAX, Python
Responsibilities
Lead development of computer vision methods for quantifying motor abnormalities from video; Develop pipelines for pose estimation, landmark detection, and movement segmentation; Design and evaluate ML/DL models for gait, balance, and facial expression analysis; Investigate temporal modelling and representation learning; Integrate video features with speech and sensor data; Evaluate model robustness across sites; Collaborate with clinical teams on study design and data annotation; Prepare scientific manuscripts and present at conferences.
Seniority
Postdoctoral Researcher
