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Ludwig-Maximilians-Universität München

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Postdoctoral Researcher in NLP and AI for Business, Economic, and Related Data Ludwig-Maximilians-Universität München in Germany

Degree Level

Postdoc

Field of study

Computer Science

Funding

This is a full-time TV-L E14 postdoctoral position, also possible part-time, offered for two years and limited to December 31, 2028. The advert does not specify a separate stipend or tuition coverage.

Deadline

Nov 30, 2026

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Country

Germany

University

Ludwig-Maximilians-Universität München

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Keywords

Computer Science
Information Technology
Artificial Intelligence
Natural Language Processing
Business
Data Annotation
Economics
Statistics
Large Language Models
ML

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About this position

Ludwig-Maximilians-Universität München is seeking a Postdoctoral Researcher in NLP & AI for Business, Economic, and Related Data to join the Chair of Statistical Learning and Data Science and collaborate with the SODA lab through the BERD@NFDI consortium.

The project examines how artificial intelligence can support researchers throughout the data lifecycle, including data discovery, preparation, metadata enrichment, annotation, and analysis. The postdoctoral researcher will coordinate and implement BERD@NFDI’s AI strategy, covering natural language processing, machine learning, large language models, and potential applications of agentic AI.

The work will involve designing and evaluating ML- and LLM-based workflows for BERD@NFDI services such as the Academy, Data Portal, OCR, and Knowledge Graph Infrastructure. Particular attention will be given to LLM-generated data and data annotation, with opportunities to shape the consortium’s future direction and research-data services.

The successful researcher will work across the consortium, coordinating with task leads, contributing to project management, reporting, proposals, NFDI networking, and community visibility. The role also includes independent research and publication in machine learning and NLP, teaching in the Department of Statistics, and supervision of Ph.D. and graduate students.

SLDS develops statistically grounded and practically useful machine-learning methods, including AutoML, interpretable, causal, fair, and probabilistic learning, alongside open-source software such as mlr3 and OpenML. The SODA lab focuses on critically examining and improving the use of data in social-science research and beyond. Both groups are part of the Munich Center for Machine Learning, a large collaborative LMU–TUM research community in Munich.

Funding details

This is a full-time TV-L E14 postdoctoral position, also possible part-time, offered for two years and limited to December 31, 2028. The advert does not specify a separate stipend or tuition coverage.

What's required

Applicants must hold an excellent Ph.D. in statistics, computer science, machine learning, or a related field; have a strong background in machine learning and natural language processing, particularly large language models and text-data annotation; possess experience with advanced NLP/AI workflows such as retrieval-augmented generation, synthetic data generation or annotation, or agentic systems; have strong Python programming skills; and have publications in relevant ML, NLP, or AI venues. Eagerness to coordinate and work in teams is required, while project or team leadership experience is advantageous. Interest in research data infrastructures, FAIR principles, and open science is expected. Fluency in written and spoken English is required; German is an advantage. Applications must be in English and include a CV with the specified sections plus two referees, including the Ph.D. supervisor, with contact details.

How to apply

Prepare the application materials entirely in English as one PDF, including the requested CV sections and details for two referees, one being the Ph.D. supervisor. Email the PDF by November 30, 2026 to [email protected] with the subject line “BERD postdoc application” and your name.

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