M. Bichler
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PhD Position in Multi-Agent Learning, Optimization, and Game Theory at Technical University of Munich Technical University of Munich in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
PhD position (E13) at TUM within the ERC Advanced Grant project "Equilibrium Learning, Uncertainty, and Dynamics". The post is a salaried doctoral employment position; no stipend amount is stated.
Country
Germany
University
Technical University of Munich

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About this position
Technical University of Munich (TUM) is advertising a PhD position (E13) at the Chair of Decision Sciences and Systems in the Department of Computer Science, within the research group of Professor M. Bichler. The position is part of the ERC Advanced Grant project “Equilibrium Learning, Uncertainty, and Dynamics”.
The project sits at the intersection of multi-agent learning, machine learning, optimization, and game theory. The group highlights a collaborative environment with young colleagues, professional development support, and an attractive research setting at TUM.
Eligibility highlights: applicants should hold a university degree in computer science or mathematics, have an interest in the listed research areas, and demonstrate excellent English communication skills.
Application materials: detailed CV, all transcripts, selected publications if available, a list of references, and copies of bachelor’s and master’s theses. Applications are to be sent by email to [email protected].
Institution: Technical University of Munich, Germany.
Notes: TUM states that it is committed to equal opportunities and encourages women and individuals bringing additional dimensions of diversity to apply. The post is suitable for disabled persons, with preference given to equally qualified disabled applicants.
Funding details
PhD position (E13) at TUM within the ERC Advanced Grant project "Equilibrium Learning, Uncertainty, and Dynamics". The post is a salaried doctoral employment position; no stipend amount is stated.
What's required
Applicants should have a university degree in computer science or mathematics, an interest in machine learning, optimization, and game theory, and excellent communication skills in English. Application materials should include a detailed CV, all transcripts, selected publications if available, a list of references, and copies of bachelor's and master's theses.
How to apply
Prepare a detailed CV, transcripts, selected publications if available, references, and copies of your bachelor's and master's theses. Send the application by email to [email protected].
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