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

Constructor University Bremen gGmbH; Germany (OH); On-site; USD 19,289 - 23,105; Full time

Benefits offered by this job

Monthly stipend

Health insurance subsidy

Research-cost allowance

Mini-job allowance

Job summary

Constructor University Bremen gGmbH invites applications for a PhD position focused on AI-driven semantic structure extraction, automated reasoning-flow modeling, and adaptive content generation. The role spans research on semantic parsing, graph-based reasoning, and metacognitive prompting, with cross-disciplinary collaboration across CS, linguistics, and education.

The successful candidate will contribute to datasets, baseline models, learning engines, and cross-domain mappings, while

Qualifications

• Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field.
• 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 supporting scientific or educational use cases.

Responsibilities

• Contribute to development of AI-driven semantic structure extraction and reasoning-flow modeling.
• Develop datasets, baseline models, and personalized learning engines.
• Publish high-quality research and release prototypes for demonstrator systems.
• Engage in teaching activities in Machine Learning, NLP, AI in Education, Knowledge Representation, and Python-based seminars.

Skills

semantic parsing

graph-based reasoning

transformer models

NLP

educational AI

Python

AI research

Education

PhD in Computer Science

Tools

Python

PyTorch

TensorFlow

Job description

Organisation/Company Constructor University Bremen gGmbH Department School of Science Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 31 Aug 2026 - 18:00 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

About the position

You are expected to contribute to the development of internationally visible, foundational research in AI-driven semantic structure extraction, automated reasoning-flow modeling, and adaptive content generation. The research focuses on methods for analyzing and representing deep semantic and pedagogical structures in scientific and educational materials; high-fidelity extraction of conceptual and reasoning blocks; inference-time rationale generation; and adaptive, learner-aware sequencing of content. This includes work on semantic parsing, structured NLP, graph-based neural models, metacognitive prompting, ontology alignment across disciplines, and human-in-the-loop optimization.

In this context, interdisciplinary research is strongly encouraged—particularly collaborations spanning computer science, computational linguistics, cognitive science, and the learning sciences. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve system interpretability and instructional quality. The successful candidate will also contribute to high-quality publications, release research prototypes, and support demonstrator systems that deliver structured semantic extraction, rationale-aware content generation, and cross-domain transfer of reasoning structures.

Additionally, the successful candidate is expected to support teaching activities in areas such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in course delivery, advising students, supervising Bachelor/Master theses, and engaging in methodological innovation for online, hybrid, and in-person learning environments. The university provides strong support for early-career researchers, including mentorship, administrative assistance, access to computational resources, conference funding, and opportunities to collaborate with other research groups and industrial partners working at the intersection of AI and digital education.

Mandatory 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 one or more of the following areas:
  • semantic parsing and structured representation learning
  • knowledge graphs or graph-based reasoning
  • transformer models, sequence modeling, or GNNs
  • natural language generation and explainability
  • 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 supporting scientific or educational use cases.
• Responsible, self-motivated, and capable of working independently as well as 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.

Funding & Appointment Terms

The appointment provides full financial coverage through a dedicated fellowship, comprising:

• Monthly stipend of €1,650
• Monthly research-cost allowance of €100 (Forschungskostenpauschale)
• Health-insurance subsidy of €100 per month
• Supplementary €603 mini-job allowance to support parallel part-time employment (optional)

AI for Semantic Structurese:

• Academic transcripts;
• A detailed letter of motivation outlining research interests and career goals;

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