Master Thesis "Meta Learning in Nonlineary Dynamic System Modelling"

Master Thesis "Meta Learning in Nonlineary Dynamic System Modelling"

CENTER FOR VISION, AUTOMATION & CONTROL

As Austria's largest research and technology organisation for applied research, AIT Austrian Institute of Technology is dedicated to make substantial contributions to solving the major challenges of our time, climate change and digitalisation.

Our Center for Vision, Automation & Control located in Vienna invites applications for a master's thesis. The Center exploits the opportunities provided by automation and digitalisation to initiate and advance innovation for industry, primarily in Austria and Europe.

For this master's thesis you will join our Competence Unit Complex Dynamical Systems, which focuses on the development and deployment of algorithms to control various types of systems.

Your Tasks

• The focus of this master's thesis is the investigation of meta learning techniques for fast model adaptation in low-data scenarios.
• You will support data-driven modeling and identification of nonlinear dynamical systems.
• You will familiarise yourself with state-of-the-art approaches in transfer learning and meta learning for system identification through a structured literature review.
• Under the guidance of researchers, you will re-implement and evaluate selected reference methods from current research, for example in Python or MATLAB.
• You will design and develop a simulation-based validation environment to assess the performance of the implemented methods.
• You will analyse and compare the adaptability and efficiency of different approaches on nonlinear system identification tasks.
• Optionally, you will apply and validate your methods on a real-world valve test bench.
• You may publish your results in a scientific journal and present them at a conference.

Your Qualifications

• Ongoing master's studies in electronics, technical mathematics, technical informatics, data science or a comparable technical field.
• Enjoyment of application-oriented questions of industry.
• Good knowledge in Python or MATLAB.
• Good knowledge of machine learning.
• High level of commitment and team spirit.
• Very good English or German skills, spoken and written. The thesis can be completed in either language.

What To Expect

• Duration of the master's thesis project: 6 months.
• Start date: as soon as possible, with some flexibility depending on availability.
• EUR 616,44 gross per month for 12 hours per week based on the collective agreement, plus additional company benefits.
• A supportive research environment with extensive experience in supervising and guiding master's theses.
• Insights into interdisciplinary research at the intersection of machine learning, control engineering, and system identification.
• Training in scientific work and close collaboration with experts from mathematics, informatics and engineering.

For further information please contact: DI Markus Gurtner, markus.gurtner@ait.ac.at.

Apply now!