Doctoral Research Associate in Human-AI Collaboration for Software Engineering (TV-L E13 %)
24.07., Wissenschaftliches Personal
The Chair of Software Engineering & AI is searching for a new doctoral research associate (TVL-E13) in Human-AI Collaboration for Software Engineering.
Research Focus
The rise of powerful Large Language Models (LLMs) and autonomous AI agents is set to fundamentally change the practice of software engineering. As AI evolves from simple co-pilots to agents capable of understanding entire project contexts and executing complex tasks, a critical gap emerges: How do developers effectively interact with, delegate to, and validate the work of these powerful new tools?
This research area sits at the intersection of Human-Computer Interaction (HCI), Artificial Intelligence (AI), and Software Engineering (SE). The goal is to design and evaluate new interaction patterns and workflows that make human-AI collaboration seamless, trustworthy, and effective. This includes exploring emerging paradigms like "vibe coding", where the developer's role shifts to specifying high-level requirements and intent while relying on the AI to handle the code generation. The research will bridge the gap between AI's potential and its practical application in real-world development environments.
Your Tasks
Given this transformation in software development, we aim to explore the following topics:
1. How do software engineers effectively instruct and delegate complex development tasks (e.g., feature implementation, debugging) to autonomous AI agents?
2. What new interaction patterns and user interfaces are needed to help developers manage, understand, and trust the outputs of AI systems operating on large codebases?
3. How can we design AI-powered tools that make their reasoning processes transparent and their results verifiable for human developers?
4. Can we develop quantitative and qualitative metrics to measure the effectiveness and usability of different human-AI collaboration models in software engineering?
5. How can we support not only professional developers but also novice programmers in creating one-time or customized small software solutions through intuitive, "vibe-coding" or intent-driven interaction with AI?
6. What are the foundational principles of "vibe-coding"? How can we design and evaluate the interaction models that best translate a user's high-level intent or "vibe" into functional, reliable code?
7. What actionable guidelines can be established to help software development teams integrate these novel collaboration patterns into their existing workflows and tools?
Working alongside Prof. Chunyang Chen and Ludwig Felder, M.Sc., the successful candidate will develop and apply new methods at the intersection of HCI, AI, and SE, while supporting all ongoing projects in this area. This PhD position is partially funded by Ludwig Felder's BMFTR-funded Software Campus project. The position is located at the TUM Campus Heilbronn.
Your qualifications
8. A strong background in computer science, AI, HCI, SE, or a related field.
9. A solid understanding of software engineering principles and development practices is essential.
10. Good programming skills in at least one programming language (e.g., Python).
11. Experience with machine learning, LLMs, or HCI/user study methodologies will be a plus.
12. Strong interest in acquiring and developing new methods and techniques.
13. Skilled in cross-disciplinary research within an international collaborative environment.
14. Proficient written and spoken skills in English and German.
15. Participation in the supervision of university teaching; the teaching and research language is English.
We offer you
At TUM Campus Heilbronn, you'll find an exciting and challenging project within a dynamic and collaborative research environment. Our long-standing and internationally recognized expertise in the field, coupled with close collaborations with academic and industrial laboratories worldwide, ensures access to rich, high-quality experimental data based on state-of-the-art technologies.
Salary is paid according to remuneration group E13 TV-L (%) of the pay scale for the German public sector. This is a position for a Doctoral student. TUM is an equal-opportunity employer. Therefore, women are especially encouraged to apply. We hope this position can start in late .
Applications
Complete applications should be sent to. To ensure your application is directed correctly, please use the following subject line format for your email: [Doctoral Application] Human-AI Collaboration for SE. Please include a CV, a cover letter explaining why you are interested in the position and how you fit the profile, a brief summary of previous work experience, and the contact information of at least two referees.
The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.
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