Master Thesis in AI Agents

30.07.2025, Abschlussarbeiten, Bachelor- und Masterarbeiten

Are you curious about the future of neural network architectures beyond transformers? Are you excited by breakthroughs like Mamba and xLSTM that are faster and more efficient for long sequences? This project aims to push the limits of memory capacity and performance by enhancing these innovative models and bringing real-world improvements over standard transformers. Are you ready to explore this new research direction that has great potential? We are interested in supervising talented students and publishing high-quality publications with practical applications. Our lab is led by Prof. Volker Tresp from LMU, who is one of PIs of a European Laboratory for Learning and Intelligent Systems (ELLIS) fellowship program and the first distinguished research scientist at Siemens Corporate Technology, and PI of Munich Center of Machine Learning (MCML). We have already published several high-quality publications at top international conferences (Neurips, ICLR, ACL, EMNLP, NAACL, AAAI, UAI, CIKM, etc.). During this thesis project, you can collaborate with many talented PhDs. You will have the opportunity to develop advanced research skills while exploring the exciting field of Linear Attention Transformers.

Topic Description:
Concrete topics include Linear Attention Transformers, State-Space models, Large Language Models, etc.

Requirements:
● Study (Bachelor/Master) in computer science, electrical engineering, physics, or mathematics;
● Good understanding of machine learning and deep learning;
● Good understanding of transformer as a plus;
● Good programming skills in Python and at least one deep learning framework;
● Independent working

Additional Information:
Start: from now on
Length of the work: 6-9 months

Contact information:
If you are interested, please contact yakov.golovanev@gmail.com

We are looking forward to hearing from you!

Kontakt: cognitive.yunpu@gmail.com