HAICC – Human-AI Collaboration for Cybersecurity redefines how humans and AI agents cooperate to tackle the most demanding cybersecurity problems. Instead of pursuing fully autonomous AI, HAICC develops co-constructive frameworks that integrate the strengths of both human experts and intelligent AI agents.
The project builds on the HAI-Co² framework for expert–AI co-construction [1], in which experts and AI agents iteratively develop and refine solutions. HAICC extends this paradigm to cybersecurity – a high-stakes, knowledge-intensive domain where trust, transparency, and integrity are essential.
The goals include:
- Agentic architectures for cybersecurity.
- Designing HCI-based interaction protocols and data collection for expert–AI collaboration in cybersecurity.
- Learning expert preferences from natural language feedback.
- Multimodal domain-specific adaptation through efficient, data-sparse learning methods.
- AI agent integrity and accountability.
HAICC is a collaborative interdisciplinary research effort at the Technical University of Darmstadt and the Univ. of Frankfurt, bridging artificial intelligence, cybersecurity, and human–computer interaction. The PI team includes a diverse team of leading researchers: Prof. Dr. Iryna Gurevych (Spokesperson, Natural Language Processing), Prof. Dr. Kristian Kersting (Machine Learning), Prof. Dr. Carsten Binnig (Multimodal AI), Subhabrata Dutta, PhD (Natural Language Processing), Prof. Dr. Mira Mezini (Software engineering), Prof. Dr. Florian Müller (Human-Computer Interaction), Prof. Dr. Christian Reuter (Cybersecurity), Prof. Dr. Haya Schulmann (Cybersecurity), Prof. Dr. Anna Rohrbach (Multimodal AI), Prof. Dr. Markus Rohrbach (Multimodal AI), Prof. Stefan Roth (Computer Vision), Prof. Dr. Michael Waidner (Cybersecurity). Prof. Dr. Hinrich Schütze (Natural Language Processing) from the LMU Munich is affiliated with the project. Each PhD student will be co-supervised by at least two faculties.
The project is funded by the National Research Center for Applied Cybersecurity ATHENE and affiliated with the Hessian Center for Artificial Intelligence (hessian.AI). It benefits from access to cutting-edge infrastructure including TU Darmstadt’s GPU clusters (A100 and H100) and collaborations within the university’s strong AI and cybersecurity ecosystem.
[1] Subhabrata Dutta, Timo Kaufmann, Goran Glavaš, Ivan Habernal, Kristian Kersting, Frauke Kreuter, Mira Mezini, Iryna Gurevych, Eyke Hüllermeier, Hinrich Schütze; Problem Solving Through Human–AI Preference-based Cooperation. Computational Linguistics 2025; doi: https://doi.org/10.1162/COLI.a.19
Your tasks
Depending on your profile, your work may focus on one or more of the following areas. Across all areas, you will collaborate closely with leading researchers in AI, cybersecurity, and HCI at ATHENE, publish in top-tier venues, and contribute to building a new paradigm for Agentic Cybersecurity and trustworthy Human–AI Collaboration.
- Human–AI collaboration
- Investigate real-world cybersecurity workflows (e.g., in SOCs, CERTs, or IT-security teams) using empirical HCI methods such as contextual inquiry and cognitive task analysis. Identify cognitive bottlenecks and opportunities for AI support, and co-design data collection, new protocols and interfaces for effective expert–AI cooperation.
- AI agent foundations
- Develop the core capabilities of collaborative AI agents — including natural-language understanding, preference learning, and domain-aware reasoning — that enable co-construction of cybersecurity solutions. Research adaptation techniques for LLM-based agents to learn expert preferences and to operate reliably under data sparsity.
- Multimodal adaptation
- Extend language-based AI agents to reason over multiple modalities such as tabular network data, images, and code. Design unified representations that allow agents to connect these data forms seamlessly during cybersecurity analysis and decision-making.
- AI integrity and trustworthiness
- Formalize and implement the principles of explainability, advisability, and controllability in cooperative AI agents. Explore neuro-symbolic and interactive learning methods that allow experts to understand, verify, and guide AI behavior in high-stakes security contexts.
- Cybersecurity applications and evaluation
- Apply the HAICC framework to concrete use cases such as access-control policy design, configuration management, or cross-application threat monitoring. Build prototypes, conduct benchmarking and human-in-the-loop evaluations, and assess the real-world value of human–AI co-construction.
Your profile
- Master’s degree (for PhD) or PhD (for postdoc) in computer science, artificial intelligence, cybersecurity, human–computer interaction, or related fields.
- Strong background in one or more of the following areas:
- Large Language Models, NLP and AI agents
- Cybersecurity or security analytics
- Machine learning and preference learning
- Human–AI interaction or explainable AI
- Excellent programming and experimental skills.
- Strong analytical and communication abilities; motivation for interdisciplinary collaboration.
- Very good English skills (German is a plus but not required).
How to apply To ensure your application reaches the correct project, follow these steps:
- Visit the official application portal: https://careers.ukp.informatik.tu-darmstadt.de/
- Complete the online form with your personal information and uploaded materials.
- Under the position selection section, choose the “ATHENE-HAICC” position specifically. This is essential; your application will only be considered for this project if this option is selected.
- The application documents must include: a motivation letter, your detailed CV, degree documents incl. transcripts of studies, a project proposal (up to three pages), your preferences regarding the work area(s) and supervisor(s), recommendation letters.
The application deadline is Sunday, December 14th, 2025. Positions remain open until filled.
We offer
- Technical University of Darmstadt offers varied and challenging assignments, freedom to work independently, the latest technologies, good collaboration between colleagues in partnership, needs-based training opportunities, and customised personnel development.
- Opportunity for further qualification (doctoral dissertation) is given. The fulfillment of the duties likewise enables the scientific qualifications of the candidate.
- Development and organisation – comprehensive in-house training offers, including the opportunity for continuing education and development;
- Annual leave/educational leave – 30 days annual leave (full-time employment) and 5 days educational leave;
- Sustainable and mobile – eligibility to free public transport in the state of Hesse with the LandesTicket Hessen (Hesse StateTicket) in accordance with the currently valid collective agreement, in addition to opportunities to work remotely at times;
- Fit and healthy – free of charge preventive medical check-ups and a wide-ranging subsidised sports programme;
- Work-life balance – flexible working time models, plus BGM (Betriebliches Gesundheitsmanagement – University Health Management);
- Pension scheme – supplementary public service pension scheme (VBL) in accordance with the currently applicable regulations;
- University bicycle;
- Family-friendliness/compatibility of family/care/career – (university-run) childcare services, child allowance (based on the collective agreement), childcare programmes during school holidays.
General information, data privacy
TU Darmstadt intends to increase the number of female employees and encourages female candidates to apply. In cases of equal qualifications, applicants with a degree of disability of at least 50% or equivalent will be given preference. Remuneration is in accordance with the collective agreement for the Technical University of Darmstadt (TV – TU Darmstadt). Part-time employment is generally possible.
By submitting your application, you agree that your data may be stored and processed for the purpose of filling the vacancy. You can find our privacy policy on our webpage.
