Postdoctoral Researcher: AI for Semantic Structures, Reasoning Flows & Personalized Content Generation

The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course development and supervising Bachelor’s, Master’s, and PhD theses. The university provides a supportive academic environment—including mentoring, administrative support, computational resources, and opportunities for technology transfer and industry engagement—enabling the postdoctoral researcher to establish or strengthen an internationally visible research profile.

Mandatory requirements

• PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a closely related field.
• Strong publication record in relevant top-tier venues (e.g., NeurIPS, ACL, ICML, ICLR, AIED, LAK, AAAI).
• Demonstrated expertise in at least two of the following areas:
• semantic parsing or structured NLP
• knowledge representation, reasoning graphs, or GNNs
• natural language generation, explainability, or rationale modeling
• ontology alignment, cross-domain transfer, or representation learning
• personalization algorithms, metacognition, or educational AI
• human-in-the-loop systems or RLHF
• Experience in leading research tasks, mentoring junior researchers, and coordinating multi-stage projects.
• Fluency in Python and modern deep learning frameworks (PyTorch/TensorFlow).
• Strong analytical, communication, and academic writing skills.
• Demonstrable ability to design rigorous experimental pipelines and validation methodologies.
• Responsible, independent, and proactive research personality with strong teamwork skills.
• Intercultural experience and readiness to work in an international research environment.
• Fluency with AI co-pilot assistants for coding and writing.
• Fluency in English, the primary language of research and instruction on campus.

Preferred qualifications:

• Experience in developing research prototypes, evaluation benchmarks, or large-scale datasets.
• Prior involvement in interdisciplinary or applied research projects.
• Potential to contribute to competitive funding applications.
• Experience with open-source releases or reproducible research pipelines.

Application Details

• Starting date: September , 2026
• Contract: Full-time (100%), TV-L E13
• Work mode: Hybrid

Application package must include:

• Curriculum Vitae (CV);
• A detailed letter of motivation outlining research interests and career goals;
• 2 recommendation letters;

Applications to be reviewed on a rolling basis. Shortlisted candidates  will be invited to interviews.

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