Research assistant - 0.75 working time

The Brains, Bots, and Minds Lab at Technische Universität Berlin, directed by Prof. Dr. Eva Wiese, is seeking a highly motivated researcher. Our research focuses on the cognitive neuroscience of human–robot interaction, combining EEG/ERP methods, cognitive modeling, and behavioral paradigms targeting visual attention and working memory. We integrate empirical research with a strong interest in fundamental and contemporary questions regarding human-machine interaction, and we prioritize open, transparent, and reproducible science in the spirit of Open Science. Close collaboration within an international, interdisciplinary team is central to our way of working. We value collegial and respectful exchange, mutual support, personal initiative, and a high level of motivation to jointly advance empirical research questions.
The successful candidate will be supervised by Prof. Dr. Eva Wiese and Dr. Tobias Feldmann-Wüstefeld within the DFG-funded project “Neural correlates of trust in human-AI interaction.” The project offers the opportunity to pursue a doctorate.

• Designing, conducting, and analyzing behavioral and neurophysiological experiments on topics, such as human–robot interaction, human–AI interaction, cognitive offloading, and social artificial intelligence
• Developing and implementing experimental paradigms using EEG/ERP, eye-tracking, and computational or cognitive modeling, including multivariate and machine-learning-based analysis methods
• Programming and integrating AI-based components (e.g., language models) into experimental paradigms, as well as data-driven adaptation of adaptive systems
• Collaborating with researchers across different disciplines including cognitive neuroscience, AI, robotics, and human–computer interaction
• Preparing, writing, and publishing scientific articles in peer-reviewed journals
• Presenting research findings at international conferences
• Supporting general lab activities, data management, and open-science practices

• Successfully completed academic university degree (Diplom, Master or equivalent) in one of the following fields: experimental psychology, cognitive or social neuroscience, or cognitive science
• In-depth knowledge of experiment programming (e.g., using PsychoPy, Matlab Psychtoolbox) and the collection of EEG and behavioral data
• In-depth knowledge of behavioral data analysis (e.g., using R) and EEG data analysis (e.g., using EEGLAB, Brain Vision Analyzer)
• Proficiency in at least two of the following EEG methods: event-related potentials (ERPs), frequency-based EEG analyses, multivariate EEG methods, or EEG modeling using machine learning
• Initial experience with AI programming (e.g., integrating language models into experimental environments, data-driven adaptation of adaptive systems)
• Excellent scientific writing and presentation skills, demonstrated by publications and/or conference contributions
• Excellent spoken and written English skills
• Experience in the collection and analysis of eye-tracking data desirable
• Experience in drafting ethics applications is a plus

Please send your application with the reference number and the usual documents only by email (combined in a single pdf file) to Prof. Dr. Eva Wiese via christin.@seideltu-berlin.de).

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guarantee for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.