Projektassistent inom Integrativ Neurofysiolog
Core
Developing an automated platform for analyzing daily activities (ADL) using video and motion data to study human behavior in realistic home environments for applications in neurology, rehabilitation, and aging.
Role type
Research Assistant (Computer Vision & Machine Learning)
Builds
Automated analysis pipeline for markerless 3D pose estimation and activity recognition
Domain
Neuroscience, Biomechanics, Artificial Intelligence
Deliverable
production ML models
Required skills
Python programming, Machine Learning, Signal Processing, 2D/3D pose estimation, Activity recognition, Video annotation, Model validation
Preferred skills
Computer Vision, Deep Learning frameworks (PyTorch/TensorFlow), Experimental data collection, Motion capture, Large dataset handling, Scientific programming
Technologies
Python, PyTorch, TensorFlow, Multicamera systems
Responsibilities
Implement and adapt algorithms for 2D/3D pose estimation, Develop methods for activity recognition and segmentation, Record video with subjects, Annotate large video-based datasets, Evaluate and validate models against experimental data, Document results
Seniority
Junior, hands-on IC