Two researcher/PhD student positions at the Social Cognitive Systems Group of CITEC/Faculty of Technology, Bielefeld University
The Social Cognitive Systems Group (Prof. Stefan Kopp; https://scs.techfak.uni-bielefeld.de <https://scs.techfak.uni-bielefeld.de/> ) is seeking highly motivated candidates for two researcher/PhD student positions (TVL E13 100%) to be filled as soon as possible and for the next three (or more) years:
**** Researcher and faculty staff in the SCS group (three years with possible extension)
You are part of the core staff of the research group, involved in the research, teaching, and
(partly) administrative activities of the group. Regarding research, you will actively contribute to the group’s research on machine learning-based methods for human-aware A.I. (e.g. in the form of intelligent assistants and collaborative or socially assistive robots). You can make use of the group’s excellent lab infrastructure at CITEC. Your specific research topic can be determined in accordance with the group’s agenda and you will be encouraged to obtain a PhD degree on this. You teaching will involve organizing tutorials, seminars, or student projects and supervising BSc/MSc theses in Cognitive Computer Science or Intelligent Systems. You will be hired for three years, with a possible extension of two more years.
**** Research assistant/PhD student in A.I. network SAIL
You are part of the research network SAIL (SustAInable Life-cycle of Intelligent Socio-Technical Systems; https://jaii.eu/sail/), funded by the Ministry of Culture and Science of the state of North Rhine-Westphalia, and run by Bielefeld U and U of Paderborn together with two other universities of applied science in East Westphalia. You will be working on the subproject “Long-term interaction memories for teachable assistance”, mainly coordinated by the SCS group but carried out in collaboration with colleagues from U of Paderborn (Prof. K. Rohlfing; Psycholinguistics). Your task is to develop ML-based representations for interaction memories of assistive systems that can support people with special needs. The goal is realize a virtual „teachable” personal assistant that builds up an interaction memory with a user (using natural language processing and demonstrations) and employs it for selecting assistive behavior in related situations, respecting privacy concerns. This work will possibly be carried out in cooperation with regional care homes.