Technical University of Munich, Centre for Mathematics
Position ID:
TUM-PHD_MF [#27306]
Position Title:
Doctoral Position in “Optimal Control and Machine Learning”
Position Location:
Garching, Bayern 85748, Germany
Subject Area:
Applied and Numerical Analysis
Appl Deadline:
2025/11/19 11:59PM
(posted 2025/10/09, listed until 2025/11/19)
(posted 2025/10/09, listed until 2025/11/19)Position Description:
Position Description
Doctoral Position in “Optimal Control and Machine Learning” Technical University of Munich (TUM)Chair of Applied and Numerical Analysis – Prof. Massimo Fornasier
The Chair of Applied and Numerical Analysis at the Technical University of Munich (TUM), led by Prof. Massimo Fornasier, is seeking outstanding candidates to join the newly established graduate program "Machine Learning and Control Theory: Exploring Synergies, Complementarities and Mutual Benefits" (METEOR) of the Ludwig Maximilian University of Munich and the Technical University of Munich.
About the Project
The focus of the project is novel development of optimal control theory with applications in machine learning.
Positions Available
We invite applications for: Doctoral Researchers (Ph.D. Candidates)
This full-time position is offered for three years.
Qualifications
• Master’s degree in Mathematics.
Please note: Applications from candidates with degrees in other disciplines (e.g., Computer Science, Engineering) will not be considered.
Applicants must demonstrate:
• An excellent academic record, including top grades.
• Strong motivation, intellectual curiosity, and the ability to work independently and collaboratively.
• Solid English communication skills (spoken and written). Proficiency in German is not required.
Responsibilities include collaborative research within the team and with external partners, contribution to teaching activities, and active engagement in the broader academic life of the group.
Work Environment
The successful candidate will join the dynamic, interdisciplinary, and international graduate program "Machine Learning and Control Theory: Exploring Synergies, Complementarities and Mutual Benefits" (METEOR) and the community at the TUM Garching campus. TUM’s Department of Mathematics is part of the TUM School of Computation, Information and Technology (CIT).
More information is available at:
https://www.math.cit.tum.de/en/math/home/ ;
Employment Conditions
• Start date: April 1, 2026
• Salary: Based on the German public sector pay scale TV-L E13, commensurate with experience and qualifications.
Application Procedure
Please submit the following
documents via MathJobs.org:
- Motivation letter
- Curriculum
Vitae, including academic transcripts and a
list of publications (if applicable)
- Research
focus/interest, specify your intended focus area:
- Optimal
Control
- Theoretical
Machine Learning
- 1-2
academic reference letters (to be submitted directly through
MathJobs)
Contact
For inquiries regarding the positions, please contact:
Prof. Massimo Fornasier – massimo.fornasier@ma.tum.de
Review of applications will begin November 20, 2025 and will continue until the positions are filled.
As part of your application, you provide personal data to the Technical University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art. 13 of the General Data Protection Regulation of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your application, you confirm to have read and understood the data protection information provided by TUM. Find out more about us at www.tum.de.
Application Materials Required:
- Submit the following items online at this website to complete your application:
- Cover letter
- Publication list
- Letter of Motivation
- Resarch focus/ interest, specify your intended focus area: Optimal Control, Theoretical Machine Learning
- Curriculum Vitae, including academic transcripts
- Two reference letters (to be submitted online by the reference writers on this site )
- And anything else requested in the position description.
Further Info: