At the University of Bremen, in Faculty 3 – Mathematics and Computer Science – Cognitive Systems Lab (Prof. Tanja Schultz), a full-time position is available in the project “The cognitive control of social resonance” as of the next possible date (under the condition of job release).
Doctoral Position / Junior Researcher (f/m/d)
– Pay group 13 TV-L –
for a period of three years.
The fixed-term contract is for scientific qualification according to § 2 para. 1 WissZeitVG (Wissenschaftszeitvertragsgesetz). Accordingly, only applicants who still have qualification periods to the corresponding extent according to § 2 para. 1 WissZeitVG can be considered.
What you can expect: Your tasks will be integrated into the Priority Programme 2134 “The Active Self” (http://www.activeself.de/) funded by the German Research Foundation (DFG).
This project aims to investigate how we imitate other humans and how different imitation behaviours can be captured and modelled using multimodal biodata. To test our theory-based predictions, we want to create a social, interactive situation in virtual reality in which human subjects are represented by a temporally synchronised double who interacts with another avatar (the Other). Techniques from the “virtual mirror” paradigm will be used with expressive triggers for social resonance, including audio-visual and electromyographic analysis of human facial movements as well as speech-based socio-emotional responses, machine-learning-based analytic techniques, and feedback-based online responses from the Other. Based on this multimodal and multimethod approach, we aim to develop a reliable and objective (near-) real-time measure of social resonance.
Our technical approach is based on an existing interdisciplinary collaboration (computer science & psychology) that builds on current theories of event encoding (TEC). In our paradigm, we aim to investigate systematic influences on multimodal imitation behaviour, such as (1) the degree of feature-related overlap between the person’s own representation and the other person’s representation; (2) the extent to which overlapping features are perceived as situationally relevant; and (3) whether the person is in a more integrative or a more focused mode of cognitive control. Thus, we hope to gain important new insights into the cognitive control of human social resonance.
- Technical implementation of the biosignal data recordings (e.g., speech data, facial electromyography, video data)
- Analyses and machine learning based on the biosignal data collected in the project
- Publication of scientific papers (conferences, journals)
You will be based at the Cognitive Systems Lab at the University of Bremen (Germany).
What we expect:
- Above average Master’s degree in computer science or a closely related field
- Advanced knowledge and proven track record in at least one of the following research areas: machine learning, biosignal processing, speech processing, image data processing, virtual reality
- Excellent programming skills
- Interest in interdisciplinary research topics (computer science, psychology)
- Very good communication skills and ability to work in a team
- Very good knowledge of the English or German language
- We are looking forward to a committed and creative personality who drives ideas and enjoys working in a team.
The University strives to increase the proportion of women in academic life and therefore expressly encourages qualified women to apply. Severely disabled applicants are given priority if their professional and personal qualifications are essentially equal. Applications from people with a migration background are welcomed.
Dr. Dennis Küster (email@example.com) will be happy to answer any technical or organisational questions you may have.
Applications with the usual documents, quoting the reference number A232/21, should be sent by October 29th, 2021 to
Prof. Dr Tanja Schultz & Dr Dennis Küster
Cognitive Systems Lab
Computer Science, University of Bremen
Enrique-Schmidt-Straße 5, D-28359 Bremen, Germany
or by e-mail in electronic form (please as one PDF file) to the following address:
We kindly ask you to send us only copies (no portfolios) of your application documents, as we cannot return them.