Research Associate (Postdoc) in Trustworthy Artificial Intelligence (Natural Language Processing) § 28 Subsection 2 HmbHG

Research Associate (Postdoc) in Trustworthy Artificial Intelligence (Natural Language Processing) § 28 Subsection 2 HmbHG

InstitutionFaculty of Mathematics, Informatics and Natural Sciences, Department of Informatics, Department of Computer Science, Professorship of Trustworthy Artificial Intelligence

Salary level

Start date01.06.2026, fixed for a period of three years (This is a fixed-term contract in accordance with Section 2 of the academic fixed-term labor contract act [Wissenschaftszeitvertragsgesetz, WissZeitVG]).The contract provides for a maximum extension of up to three years depending on the associate’s achievements during the first stage. Providing that a position is available and that requirements have been fulfilled, the associate may apply for temporary civil servant status in accordance with Section 28 subsection 2 HmbHG.

Application deadline02.03.2026

Scope of workfull-time position suitable for part-time

Your responsibilities

Duties include teaching and research in the respective department or institute. Research associates may also pursue independent research and further academic qualifications as well as acquire teaching experience. These duties are intended to promote academic achievement. Therefore, at least one-third of set working hours will be made available for the associate’s own academic work.

The postdoctoral researcher position is based at the Professorship of Trustworthy Artificial Intelligence (formerly Professorship of Data Science), led by Prof. Dr. Anne Lauscher [1]. The group conducts fundamental and applied research on the latest generation of generative AI models and systems, with a particular emphasis on system trustworthiness. Our overarching goal is to advance the effectiveness and capabilities of modern AI systems while systematically addressing ethical and safety challenges. We are committed to developing solutions that are not only high-performing, but also environmentally sustainable, fair, inclusive, and socially responsible.

The successful candidate will contribute to both teaching and research. The position includes teaching duties of 4 * 45 minutes per week during the semester (4 LVS). Teaching responsibilities may include, for example, exercise sessions, seminars, and supervision of student theses.

In addition, the postdoctoral researcher will have the opportunity to:

• contribute to the supervision and mentoring of Ph.D. students,
• support the professorship in selected organizational and academic service tasks, and
• pursue an independent research agenda in natural language processing and artificial intelligence, closely aligned with the group's focus areas, to further qualify within their academic career.

The research is expected to result in international top-tier publications (conference and/or journal articles), for example in venues such as ACL, EMNLP, AAAI, and/or interdisciplinary outlets (e.g., FAcct).

The primary mentor of the postdoctoral researcher will be Prof. Dr. Anne Lauscher, who will be happy to answer questions about the position and the group via email.

Our team is open, dynamic, ambitious, and very well connected nationally and internationally. We strongly value diversity and explicitly encourage applications from individuals who identify as members of marginalized and underrepresented groups.

[1]

Your profile

A university degree in a relevant field, plus doctorate.

We welcome applicants with expertise in one or more of the following research directions:

• Ethical and Safe Generative AI (e.g., fairness, inclusiveness, robustness, hallucination and toxicity mitigation, alignment)
• Multilingual and Multicultural AI
• Multimodality, Agentic AI, and Multi-Agent Systems
• Model Interpretability and Explainability

In addition to your profile:

• Ph.D. degree in computer science, artificial intelligence, natural language processing, computational linguistics, linguistics, or another relevant field
• a publication record relevant to the topics listed above including top-tier publications (A or A* according to the established core ranking for cs conference publications)
• very good technical skills and knowledge, e.g., machine learning, natural language processing, large language models, Python and relevant AI frameworks (e.g., Transformers), etc.
• very good proficiency of the English language
• basic proficiency of German is a plus, but not strictly required
• teaching and supervision experience is a plus, but not strictly required
• interest and joy in seeking creative solutions

We offer

• Reliable remuneration based on wage agreements
• Continuing education opportunities
• University pensions
• Attractive location
• Flexible working hours
• Work-life balance opportunities
• Health management, EGYM Wellpass
• Educational leave
• 30 days of vacation per annum

Universität Hamburg—University of Excellence is one of the strongest research educational institutions in Germany. Our work in research, teaching, educational and knowledge exchange activities is fostering the next generation of responsible global citizens ready to tackle the global challenges facing us. Our guiding principle “Innovating and Cooperating for a Sustainable Future in a digital age” drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world. We would like to invite you to be part of our community to work with us in creating sustainable and digital change for a dynamic and pluralist society.

The University of Hamburg is committed to equity. Diversity enriches our university life, whether in our studies, research, teaching, education, or workplace. We therefore welcome all applications, regardless of gender, gender identity, sexual orientation, ethnic or social background, age, religion or belief, disability, or chronic illness.

The University of Hamburg strives to increase the number of women in academia, and encourages qualified female academics to apply.

Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.