Research Assistant - 1st qualification period (PhD candidate)

The position involves basic and applied research on the modeling and experimental investigation of situated decision-making processes in human-technology contexts within the medical domain, particularly in human-AI teams. The aim of our research is to better understand and improve decision-making processes in time-critical, uncertain, and high-risk situations, using medical decision-making scenarios as a case study.

A particular focus lies on:

• Emergency decision-making by laypeople (e.g., when using symptom checkers)
• Triage decisions made by experts in collaboration with AI systems
  Additional responsibilities include:
• Independent development, execution, and publication of interdisciplinary research projects
• Independent development (and further development) of mixed-methods approaches (e.g., through AI-supported analysis of qualitative and quantitative data)
• Contribution to grant proposals
• Teaching within the MSc Human Factors program, covering quantitative and experimental study designs (or other selected methodologies), as well as decision theories and their fields of research and application

• Successfully completed university degree (Master, Diplom, or equivalent) in Psychology/Human Factors, Cognitive Science, Computer Science, or related disciplines is required
• The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills
• Solid knowledge of decision theories and/or experimental laboratory and field research are expected
• Solid methodological expertise in the application of quantitative data analysis methods are expected
• Experience conducting research in medical/technical application domains and/or decision-making contexts are desirable
• Experience in teaching is desirable
• Experience with mixed methods and/or qualitative social research methods are desirable
• Experience with and interest in the AI-based analysis of quantitative and/or qualitative data
• Interest in interdisciplinary collaboration desirable
• Experience in preparing grant applications (third-party funding) is desirable
• A passion for abstract thinking and intellectual discussion is desirable

Please send your complete application with the reference number and the usual documents (letter of motivation, curriculum vitae, certificates) combined in a single pdf file, max. 5 MB to Prof. Dr. Feufel via sekretariat@awb.tu-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 guaranty 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.