Postdoctoral Researcher: AI for Semantic Structures, Reasoning Flows & Personalized Content Gen[...]

Constructor University Bremen gGmbH; Germany (OH); On-site; USD 59,859 - 82,882; Full time

Benefits offered by this job

Mentoring opportunities

Computational resources

Industry collaboration opportunities

Job summary

Constructor University Bremen gGmbH in Germany invites applications for a postdoctoral researcher in AI-driven semantic analysis and automated reasoning-flow modeling. You will lead internationally competitive research on semantic structure extraction and rationale-aware content generation.

You will supervise PhD students, coordinate multi-stage experiments, contribute to end-to-end demonstrator systems, and publish survey and methodology papers.

Qualifications

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or closely related field.
• Strong publication record in top-tier venues (e.g., NeurIPS, ACL, ICML, ICLR, AIED, LAK, AAAI).
• Experience in leading research tasks, mentoring junior researchers, and coordinating multi-stage projects.
• Fluency in Python and modern deep learning frameworks (PyTorch/TensorFlow).
• Intercultural experience and readiness to work in an international research environment.
• Fluency in English, the primary language of research and instruction on campus.

Responsibilities

• Lead design of experiments and research directions.
• Mentor junior researchers and supervise PhD students.
• Develop end-to-end demonstrator systems with structured, rationale-rich content.
• Coordinate data annotation and evaluation frameworks.
• Publish survey papers, methodology papers, and cross-domain transfer studies.

Skills

semantic parsing

knowledge representation

GNNs

natural language generation

RLHF

metacognition

educational AI

Python

PyTorch

TensorFlow

experimental pipelines

Education

PhD in Computer Science or related field

Tools

PyTorch

TensorFlow

Job description

Organisation/Company Constructor University Bremen gGmbH Department School of Science Research Field Computer science Researcher Profile Recognised Researcher (R2) Positions Postdoc 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 conduct and lead internationally competitive research in AI-driven semantic analysis and automated reasoning-flow modeling, with applications to educational materials, scientific documents, and research authoring. Your work will focus on developing advanced methods for semantic structure extraction, conceptual and argumentative flow reconstruction, rationale-aware content generation, metacognitive prompting, and adaptive personalization. Core research contributions will include designing algorithms for concept and structure extraction, building neural/graph hybrid models for pedagogical reasoning, implementing ontology-alignment methods for cross-domain transfer, and creating human-in-the-loop optimization pipelines that incorporate expert feedback—aligning with the multi-year research roadmap (WP1–WP3) .

As a postdoctoral researcher, you will take a leading role in designing experiments, shaping research directions, supervising junior researchers (including PhD students), and contributing to the development of end-to-end demonstrator systems capable of generating structured, rationale-rich, and learner-adaptive content. You will be responsible for coordinating data annotation efforts, overseeing the construction of evaluation frameworks, and driving publication-quality research outputs, including survey papers, methodology papers, and cross-domain transfer studies. Interdisciplinary collaboration is strongly encouraged, especially at the intersection of computer science, computational linguistics, cognitive science, and learning technologies, and you will have opportunities to initiate or co-lead joint projects with internal and external partners.

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.
• Contract: Full-time (100%), TV-L E13