PhD Researcher: AI for Semantic Structures, Reasoning Flows & Personalized Content Generation(m/w/x)

Requirements

• Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field
• Strong research interest and practical experience in specified areas
• Experience in semantic parsing and structured representation learning
• Experience in knowledge graphs or graph-based reasoning
• Experience in transformer models, sequence modeling, or GNNs
• Experience in natural language generation and explainability
• Experience in educational AI, personalization algorithms, or cognitive modeling
• Evidence of research potential through publications, a strong thesis, or significant projects
• Experience or interest in innovative teaching and learning approaches
• Ability to translate theoretical insights into engineered prototypes and systems
• Responsibility, self-motivation, and capability to work independently and collaboratively
• Excellent verbal and written communication skills
• Intercultural competence and experience in international environments
• Fluency with co-pilot tools for coding and writing
• Fluency in English, the language of instruction and communication on campus

Tasks

• Contribute to foundational research in AI-driven semantic structure extraction
• Develop automated reasoning-flow models
• Create adaptive content generation methods
• Analyze and represent deep semantic and pedagogical structures
• Extract conceptual and reasoning blocks with high fidelity
• Generate inference-time rationale
• Sequence content in a learner-aware manner
• Work on semantic parsing and structured NLP
• Develop graph-based neural models
• Implement metacognitive prompting techniques
• Align ontologies across disciplines
• Optimize systems with human-in-the-loop approaches
• Develop datasets and baseline models
• Create personalized learning engines
• Design reasoning-graph representations
• Implement cross-domain mapping algorithms
• Establish RLHF-style feedback loops for system interpretability
• Publish high-quality research findings
• Release research prototypes and demonstrator systems
• Support structured semantic extraction and rationale-aware content generation
• Assist in teaching Machine Learning and Natural Language Processing
• Engage in course delivery and student advising
• Supervise Bachelor and Master theses
• Innovate methodologies for online, hybrid, and in-person learning

Work Experience

Education

Languages