Overview
The Research Training Group (RTG) METEOR is offering exciting opportunities for aspiring researchers in the fields of machine learning and control theory. This initiative, a collaboration between the University of Munich (LMU) and the Technical University of Munich (TUM), aims to cultivate a new generation of experts at the intersection of these dynamic fields. With a focus on complex dynamical systems, METEOR is set to provide fully funded PhD and postdoctoral positions, making it a significant opportunity for those looking to advance their academic careers.
Background & Relevance
Machine learning and control theory are increasingly intertwined, particularly in the context of complex systems where uncertainty and dynamic behavior play critical roles. Understanding how to model these systems effectively can lead to advancements in various applications, from robotics to autonomous systems. The METEOR initiative is positioned to address these challenges, fostering research that explores the synergies between machine learning and control methodologies. This relevance is underscored by the growing demand for solutions that can adapt to and manage uncertainty in real-world applications.
Key Details
- Positions Available: 10 PhD positions and 2 postdoctoral positions
- Funding: Fully funded, ranked according to the German TV-L E13 scale (100%)
- Duration: 4 years for PhD candidates; 3 years for postdoctoral researchers
- Start Date: April 2026
- Research Themes:
- Modeling and Quantification of Uncertainty for Robust Control
- Representation for Dynamical Systems and Control
- Control Theory for Machine Learning Algorithm Design
- Formal Analysis of Machine Learning Algorithms via Control Theory
- Website: METEOR Website
- Application Deadline: November 13th
- Application Link: Application Portal
Eligibility & Participation
These positions are targeted at individuals with a strong background in machine learning, control theory, or related fields. Candidates should possess the necessary qualifications to engage in advanced research and contribute to the ongoing projects within the RTG. This opportunity is ideal for those looking to deepen their expertise and make significant contributions to the field.
Submission or Application Guidelines
Interested candidates should prepare their applications and submit them through the provided application portal. Ensure that all required documents are included and submitted before the deadline to be considered for these prestigious positions.
Additional Context / Real-World Relevance
The integration of machine learning with control theory has profound implications for various industries, including robotics, aerospace, and automotive sectors. By training researchers in this interdisciplinary approach, METEOR aims to produce experts who can tackle complex challenges and innovate solutions that enhance the performance and reliability of systems in real-world scenarios.
Conclusion
The METEOR initiative represents a remarkable opportunity for researchers eager to explore the intersection of machine learning and control theory. With fully funded positions available, prospective candidates are encouraged to apply and contribute to groundbreaking research that promises to shape the future of these fields. Explore this opportunity and consider applying to join a vibrant research community in Munich.
Category: PhD & Postdoc Positions
Tags: machine learning, control theory, dynamical systems, munich, research training group, lmU, tum, german research foundation, uncertainty modeling, algorithm design
