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This internship is embedded within an active PhD research project aimed at building a robust multimodal perception module for Human-Robot Interaction (HRI). The research focuses on estimating high-level user states (such as attention, engagement, or confusion) by processing real-time, non-verbal cues like gaze direction or head pose.
Job Responsibility:
Take ownership of a specific part of the perception pipeline
Data Annotation & Ground Truth Creation
Model Training & Evaluation
Data Collection
Collaborate with the PhD supervisor to ensure the work contributes directly to an upcoming research paper
Requirements:
Master's student in Computer Science, Machine Learning, Robotics, or related fields
Strong proficiency in Python
Ideally, experience with Annotation Software (e.g., CVAT)
Basic understanding of Machine Learning and Computer Vision concepts (prior exposure to gaze tracking, head pose estimation, or facial landmark detection is a strong plus)
Eligible to work in Sweden with an active residency
Nice to have:
Experience with Annotation Software (e.g., CVAT)
Prior exposure to gaze tracking, head pose estimation, or facial landmark detection
What we offer:
Mentorship
Learning opportunities
Hands-on experience
Support for living expenses, relocation, etc., based on individual circumstances