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Ludwig-Maximilians-Universität München

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PhD Research Position in Artificial Intelligence and Causal Machine Learning at LMU Munich Ludwig-Maximilians-Universität München in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

The position is a full-time research position remunerated according to TV-L E13. It is initially offered for two years, with an option to extend until the end of the PhD. Part-time employment is also possible. Participation in conferences, summer schools, voluntary exchange programs, and research stays within the international partner network is supported.

Deadline

Nov 30, 2026

Country flag

Country

Germany

University

Ludwig-Maximilians-Universität München

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Keywords

Computer Science
Mathematics
Decision Making
Artificial Intelligence
Business
Uncertainty Analysis
Reinforcement Learning
Statistics
ML

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About this position

Ludwig-Maximilians-Universität München (LMU Munich) is seeking a research-position candidate in Artificial Intelligence to join the Institute of Artificial Intelligence in Management within the Munich School of Management and the Faculty of Mathematics, Informatics, and Statistics.

The research team is led by Prof. Stefan Feuerriegel and brings together international researchers from machine learning, statistics, economics, and engineering. The group develops, implements, and evaluates AI algorithms designed to improve data-driven decision-making, with links to the Causal ML Lab at LMU Munich.

PhD researchers may pursue a method track, an application track, or a combination of both. The method track focuses on causal machine learning and related areas, including causal representation learning, reinforcement learning, off-policy evaluation and learning, probabilistic machine learning, diffusion models, Bayesian methods, and uncertainty quantification. The work is oriented toward contributions to leading AI and machine learning venues such as NeurIPS, ICML, AISTATS, and KDD.

The application track investigates how AI and machine learning can advance decision-making in areas including medicine, sustainability, marketing, business, and human-AI collaboration. Projects may examine AI and machine learning for medical decision-making, AI for sustainable development, business applications, and the practical value created by new AI tools. Researchers can also collaborate with international partners, including institutions such as Harvard Medical School and the Cambridge Centre for AI in Medicine.

The role is strongly research-centered, while also providing opportunities to teach undergraduate or graduate courses and supervise student theses. Researchers join a diverse and international environment in central Munich, with access to conferences, summer schools, exchange opportunities, and potential research visits within the group’s international network. The institute welcomes independent research proposals and further ideas.

Funding details

The position is a full-time research position remunerated according to TV-L E13. It is initially offered for two years, with an option to extend until the end of the PhD. Part-time employment is also possible. Participation in conferences, summer schools, voluntary exchange programs, and research stays within the international partner network is supported.

What's required

Applicants must hold a Master’s degree in Mathematics, Statistics, Computer Science, Data Science, or Machine Learning. Fluency in English is required. Candidates should be highly motivated, passionate about research, and driven to make contributions in artificial intelligence. A CV and transcript are required; cover letters, internship reports, and certificates are not required.

How to apply

Submit your CV and transcript by email to [email protected] no later than 30 November 2026. A cover letter, internship reports, and certificates are not required.

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