University Assistant (Predoctoral) in Computer Science Education
Join a pioneering research group to advance computational thinking and AI literacy in education through empirical research and teaching innovation.
Best for:Best for recent master’s graduates in computer science, education, or related fields with a passion for empirical research and teaching innovation in computational thinking and AI literacy.
Overview
This predoctoral position at the University of Vienna focuses on computer science education, particularly computational thinking and AI literacy. The role involves conducting empirical research on teaching and learning processes, developing educational workshops, and contributing to a newly established research group. The successful candidate will work within the Computer Science Teaching and Learning Lab, collaborate with schools, and integrate into the UniVie Doctoral School of Computer Science. The position offers a unique opportunity to shape the future of computer science education while pursuing a cumulative dissertation in the field.
What you'll do
- Conduct original research on teaching and learning processes in computational thinking and AI literacy, focusing on problem-solving, abstraction, modeling, and pattern recognition.
- Design, develop, and empirically evaluate computer science education workshops and teaching-learning scenarios for both school and university contexts.
- Deliver workshops in the Computer Science Teaching and Learning Lab and collaborate with schools to implement and refine educational materials.
- Publish academic research in the form of conference papers, journal articles, and presentations based on findings from the dissertation.
- Teach independently within the scope of the collective bargaining agreement, including course development and instruction.
- Participate in research-based teaching, knowledge transfer activities, and administrative tasks within the research group.
- Finalize a dissertation agreement within the first 12 months and contribute to a cumulative dissertation in computer science education.
Requirements
Degree required: Completed Master’s degree or equivalent diploma in computer science, computer science education, teaching digital literacy, or a related field with a clear focus on computer science or computer science teaching and learning processes.
Degree offered: PhD
Language: German and English; C1 proficiency level in both languages.
Instruction: German and English
- Strong interest and passion for computer science education, AI literacy, and computational thinking.
- Willingness and ability to conduct empirical research on teaching and learning processes.
- Basic knowledge of empirical research methods or a commitment to developing these skills.
- Excellent programming and technical skills, particularly in digital tools or computer science teaching environments.
- Strong command of written and spoken German and English (C1 level).
- No explicit nationality or residency restrictions mentioned.
- No age limits or prior experience caps specified.
Funding & terms
How to apply
Deadline: 2026-10-19
Applicants must submit a scientific CV/letter of intent, a cover letter explaining their fit for the position and research field, a brief outline of potential dissertation topics (1-2 pages), proof of completion of a master’s or diploma program, an abstract of their master’s thesis, and optional documents such as a list of publications, teaching experience, or academic presentations. Applications are submitted via the university’s job portal.
- CV / letter of intent
- Cover letter explaining fit for the position and research field
- Outline of potential dissertation topics (1-2 pages)
- Proof of completion of a master’s or diploma program
- Abstract of master’s or diploma thesis
- List of publications (if available)
- Proof of teaching experience, classroom experience, project collaboration, or academic presentations (if available)
- Optional: representative writing sample (e.g., master’s thesis, seminar paper, or publication)
Contact
Bernhard Standl· Professor
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