This master thesis opportunity focuses on developing and applying deep learning techniques to improve sarcoma diagnostics. Students can explore topics such as self-supervised learning for multi-modal tumor representation, generative models for unsupervised tumor detection, and weakly-supervised learning for classification and localization.

This project focuses on generating synthetic training data for dynamic neural novel view synthesis systems. A particular emphasis is placed on creating edge case test data to evaluate the limits of current methods.

Ab sofort kann eine Masterarbeit an der Professur für Sportgeräte und Sportmaterialien (Standort Hochbrück/Forschungszentrum Garching) gestartet werden. Die experimentelle Arbeit eignet sich für Studierende aus dem Maschinenwesen, aber auch der Sportwissenschaft. Die genaue Beschreibung ist als PDF angefügt.

This thesis will focus on developing methods to protect privacy while using Large Language Models (LLMs) in automotive requirements processing. As LLMs process sensitive data, such as customer information and design specifications, ensuring that this data remains private is crucial. The research will explore anonymization techniques like data masking and pseudonymization, which hide sensitive details while keeping the data useful for LLM tasks. It will also focus on ensuring that anonymized data retains its meaning and effectiveness in the context of automotive requirements processing. For application please send me an email with title "Master Thesis Application: Data Anonymization LLM ". Please also attach your resume and transcript of records in the email. A motivation letter is NOT required.

At the lab for AI in Medicine, we offer a project on physics-based machine learning for hyperspectral neuronavigation

Large language models (LLMs) have transformed how we interact with technology, allowing users to communicate with systems using natural language. Ubuntu, a popular open-source operating system, provides a powerful environment for exploring the use of LLMs as intelligent agents. This master topic focuses on using LLMs as agents that can directly control and manage Ubuntu. The goal is to develop an LLM-based agent that can perform tasks such as configuring system settings, installing software, troubleshooting issues, and managing resources—entirely through natural language commands. This research will explore how LLMs can streamline system management, making Ubuntu more intuitive and user-friendly, while also enabling greater automation and efficiency for users at all levels. For application please send me an email with title "Master Thesis Application: An LLM-based Ubuntu User". Please also attach your resume and transcript of records in the email. An motivation letter is NOT required.

Our Research Group on Pancreatic Neuropathy and Pain is actively seeking passionate Master’s and Bachelor’s students, as well as interns, specializing in biological and chemical sciences. Our work blends molecular biology with comprehensive analysis of human pancreatic tissue, advanced 3D culture models, live cell imaging, genetically engineered mouse models (GEMMs) of pancreatic cancer, and murine models of acute and chronic pancreatitis. We operate with the Collaborative Research Center 1321 (Modelling and Targeting of Pancreatic Cancer), the DKTK (German Cancer Consortium) Munich site, the CCC München (Cancer Comprehensive Center-TZM München), and the Pancreatic Cancer Alliance Munich (PCAM). Crucially, our research is driven by insides gleaned directly from human tissue and diseases, aiming to develop in vitro and in vivo models that faithfully replicate human conditions. Comprising an international team of biologists and clinicians, our mission is to unravel key disease mechanisms in pancreatic disorders, with the ultimate aim of devising innovative therapeutic strategies. Here are our current projects: 1. Exploring the role of the exosomes in cancer cell progression and metastasis. 2. Investigating the involvement of mast cells in pain perception during acute and chronic pancreatitis 3. Examining the immunological effects of chemotherapy in pancreatic cancer. 4. Establishing of multi-cellular 3D ex-vivo systems, including organoids ad ECM scaffolds. 5. Cloning of Gene-Therapy Tools for treatment of PDAC. Our methodologies encompass a wide range of molecular biology techniques such as nucleic acid isolation, PCR, protein isolation, real-time PCR, Western blotting, cloning, bacterial transformation and plasmid isolation. We also employ cell sorting using FACS, gene editing with CRISPR Cas9, multiplex immunohistochemistry, cell culture techniques, and ECM scaffold preparation. In addition to gaining practical experience with state-of-the-art research techniques, successful candidates will have the chance to contribute to groundbreaking projects at the forefront of cancer biology and translational medicine. Join our dynamic team and help pioneer discoveries aimed at enhancing patient outcomes in pancreatic diseases. For any inquiries, please don’t hesitate to contact Dr. Rouzanna Istvánffy via e-mail at rouzanna.istvanffy@tum.de. Wenn Sie selbst eine Diplomarbeit ausschreiben wollen, lesen Sie bitte vorher unbedingt das 'Best Practice Manual Stellenanzeigen'.

Are you interested in topics such as Power to X, methanol production, CO2 capture and waste treatment? In this master's thesis, you will use Aspen Plus to simulate and optimize plant processes.

Objective The primary objective of this project is to explore how LLMs can be used to generate safety-critical scenarios within the CommonRoad framework.

We search for motivated students that want to be involved in projects assessing impacts of land use and climate change on insect diversity and biology.

The Human-Centered Computing and Extended Reality Lab of the Professorship for Machine Intelligence in Orthopedics seeks applicants for Bachelor/Master Thesis for the Summer Semester 2025.

This project aims to evaluate and benchmark existing Simultaneous Localization and Mapping (SLAM) algorithms for arthroscopic surgery, addressing challenges such as spatial orientation and navigation within the joint space. The study will focus on testing state-of-the-art camera-pose estimation techniques on arthroscopy data, analyzing their performance in terms of accuracy and robustness.

The Schuefflerlab is offering a new Master thesis Project. In this project, our objective is to develop a foundation model trained directly on IHC slides to enable more accurate automated analysis, and to facilitate downstream tasks such as staining estimation and cancer subtype classification, ultimately improving clinical decision making.

The aim of this research is to provide a catalytic formulation that generates enzymatically active surfaces for the detoxification of harmful halogenated alkanes. Toxic gases that cannot be captured by standard filtering technics such as fluorochlorohydrocarbons (CFCs) are converted into products that are harmless to the environment and health by means of enzymatic catalysis.

The Computational Pathology Lab of the TUM Institute for Pathology is offering a bachelor’s thesis titled “QC for digital pathology – scan duplicate classification”.

Are you interested in understanding how urbanization influences pollinators and pollination? We are looking for motivated students interested in chemistry, taxonomic identification, and/or ecology of insects, in particular bees.

This project aims to design an adsorption-based process for recovering and concentrating formaldehyde from aqueous solutions. By conducting experimental studies and developing adsorption models, the research will contribute to the development of an energy-efficient alternative to traditional distillation methods. Background:

Exciting opportunity for a Master’s thesis or medical doctoral thesis in Anesthesiology, in collaboration with the University of Liège (Belgium). The project aims to investigate the effects of Ketamine and Dexmedetomidine on the glymphatic clearance function of the brain using retrospective EEG and fMRI data. Experience with MATLAB or Python is required.

Wir suchen einen engagierten Masteranden, der die Programmiersprache ALDiSP weiterentwickelt. Sie studieren Informatik oder ein verwandtes Fachgebiet, verfügen über fundierte Kenntnisse in C++ und im Compilerbau und bringen idealerweise auch Erfahrungen mit LLVM, Bison und Flex mit? Dann sind sie der optimale Kandidat. Freuen Sie sich auf ein innovatives Forschungsumfeld mit modernster Technik, intensiver fachlicher Betreuung und Unterstützung bei wissenschaftlichen Publikationen.

Develop AI-driven solvers using advanced transformer architectures to accelerate brain tumor modeling for personalized radiotherapy planning.