Publisher
source

Constructor Knowledge Labs

PhD Researcher in AI for Semantic Structures, Reasoning Flows & Personalized Content Generation Constructor Knowledge Labs in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available
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Country

Germany

University

Constructor Knowledge Labs

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Keywords

Computer Science
Education
Psychology
Cognitive Science
Information Technology
Artificial Intelligence
Natural Language Processing
Computational Linguistics
Explainability
Linguistics
ML

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About this position

PhD opportunity in Artificial Intelligence, Machine Learning, Natural Language Processing, Computational Linguistics, Cognitive Science, and Education at Constructor Knowledge Labs in Bremen, Germany.

The project focuses on AI-driven semantic structure extraction, automated reasoning-flow modeling, adaptive content generation, semantic parsing, structured NLP, graph-based neural models, ontology alignment, human-in-the-loop optimization, and learner-aware sequencing of content. The successful candidate will help develop datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops for interpretable and instructional AI systems.

The role also includes teaching support in Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at BSc, MSc, and PhD levels, plus advising students and supervising theses. The post emphasizes interdisciplinary work across computer science, computational linguistics, cognitive science, and the learning sciences.

Funding: fully funded fellowship with a monthly stipend of €1,650, a €100 research-cost allowance, a €100 health-insurance subsidy, and an optional €550 mini-job allowance. The university also mentions mentorship, administrative support, computational resources, conference funding, and collaboration opportunities.

Eligibility: Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field; research experience or strong interest in semantic parsing, knowledge graphs, transformer models, sequence modeling, GNNs, explainable NLG, educational AI, personalization, or cognitive modeling; evidence of research potential; strong communication skills; intercultural competence; and English fluency.

Application: submit a CV, transcripts, motivation letter, and two recommendation letters. Applications are reviewed on a rolling basis.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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