Please apply at

https://www.scienceofintelligence.de/call-for-applications/open-positions/ref-scioi-c3-31b/

Working Field: Social responsiveness and its effects on learning in human-human and human-robot interaction

This interdisciplinary research projects combines research from educational psychology and computer vision to examine principles of social responsive teaching behaviors in social learning situations. Perceiving and appropriately reacting to social cues facilitate effective knowledge transfer between interaction participants, whether they be humans or humans and an artificial agent such as a robot. The main goal of this project therefore is to develop synthetic systems (robotic teaching assistants) with high-level perceptual capabilities in social learning situations and, in the course of that, synthetic systems that are able to simulate social responsive behaviors.

Doctoral project: “Perception, Categorization and Synthetization of social responsiveness in human-human and human-robot interaction during learning situations”

The project focuses on the identification of teaching behaviors that can be labeled as ‘social responsive’ in learning situations. We aim to automatically understand relations between social responsive teaching behaviors and student engagement, emotion, and cognitive performance in Human-Human and Human-Robot interaction. One aim is to sensitively categorize behaviors that define social responsive teaching behaviors, to synthesize such behaviors and to apply synthesized behaviors in learning situations using robotic teaching assistants.

Duties:

– Conducting experimental research in computer vision
– Analysis of video data to generate algorithms for computer vision
– Automated evaluation of behavior
– Modeling of behavior using representation and reinforcement learning
– Interaction within the SCIoI cluster of excellence
– Compilation of the results for presentations, project reports, and publications

Requirements: Applicants must hold a Diploma/Master’s degree in Computer Science or related sciences and should have proven skills/background in following topics:

– profound expertise in computer vision and machine learning
– expertise in robotics and visualization
– excellent mathematical skills,
– in depth programming skills (C/C++, Python, Matlab),
– very good command of English, both written and spoken,
– a keen interest in understanding intelligence,
– the strong communicative skills required for interdisciplinary research,
– a conscientious work approach, flexibility, good time management, and ability to work in a team

Application procedure: Candidates should upload their application preferably via the portal www.scienceofintelligence.de/jobs in order to receive full consideration.
Applications should include: motivation letter, curriculum vitae, transcripts of records (for both BSc and MSc), copies of degree certificates (BSc, MSc), abstracts of Bachelor-, Master-thesis, list of publications and one selected manuscript (if applicable), two names of qualified persons who are willing to provide references, and any documents candidates feel may help us assess their competence.