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Diplomarbeiten, Bachelor- und Masterarbeiten
Sie suchen gerade eine Diplomarbeit, ein Thema für eine Bachelor oder Master Thesis? Dann sind Sie hier richtig. In diesem Bereich sind Abschlussarbeiten aus allen Fakultäten zu finden.
Beachten Sie auch den entsprechenden Stichwortindex.
Wenn Sie selbst eine Diplomarbeit ausschreiben wollen, lesen Sie bitte vorher unbedingt das 'Best Practice Manual Stellenanzeigen'.
23.03.2026
Master’s Thesis: 3D Scene Reconstruction and Real-Time Vehicle Awareness using LiDAR from a mobile phone
Scene reconstruction and awareness of the environment are crucial in the fields of robotics, augmented reality (AR), mapping, and autonomous driving. With the integration of LiDAR sensors in smartphones, e.g., iPhone 12 Pro and later, 3D scanning is now possible without any expensive hardware. Furthermore, laser scanners can gather 3D information. This information is used to capture 3D point clouds to reconstruct a scene.
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Kontakt: tim.schreiter@tum.de
23.03.2026
Master’s Thesis: Comprehensive Facial Data and Gaze Extraction Using iPhone Front Camera and ARKit
Face and eye-gaze tracking technologies have advanced significantly with the rise of augmented reality (AR) and computer vision applications. The iPhone's TrueDepth camera, combined with Apple’s ARKit, provides a powerful tool for capturing detailed facial data and gaze information in real time.
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Kontakt: tim.schreiter@tum.de
23.03.2026
IDP/Guided Research: Anatomy-Aware Deep Learning for 2D-to-3D Orthopedic Reconstruction
Accurate 3D bone models are vital for Total Knee Arthroplasty. While deep learning can reconstruct 3D CTs from 2D X-rays, boundaries often remain blurry. The aim of this project is to improve the reconstruction. By developing a 3D bone segmentation model and integrating it as a differentiable, anatomy-aware loss, we will penalize structural inaccuracies. This prevents bone blending and enforces sharp 3D boundaries, which are required for precise surgical planning.
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Kontakt: tim.mach@tum.de
22.03.2026
Master thesis in Hydrology
Are you knowleadgeable in GIS and landscape mapping? We offer the chance to develop your skills in an interdisciplinary project mapping the hydrology of the Biodiversity Exploratories of Germany, as part of the project WaterWeb.
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Kontakt: alejandra.parreno@tum.de
22.03.2026
Masters Thesis in Soil Science
Are you interested in soil properties and how soil supports biodiversity? Then this thesis is for you! We look for a motivated student to join our projects and be part of a soil campaign across different sites in Germany. As part of the project you will be able to use existing data and produce new one to link questions on how land use change affects soils and the biodiversity that inhabits them. The project can be tailored for bachelor, master thesis and mandatory internships.
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Kontakt: alejandra.parreno@tum.de
20.03.2026
Master thesis: Adjoint Methods for Nonlinear Dynamic Problems: Expanded vs. Non-Expanded Formulation
Master thesis: Adjoint Methods for Nonlinear Dynamic Problems: Expanded vs. Non-Expanded Formulation
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Kontakt: tahar.arjoune@tum.de
18.03.2026
Abschlussarbeiten: Digitale Gesundheitsanwendungen (DiGAs)
Wir suchen Studierende für Abschlussarbeiten zum Thema Digitale Gesundheitsanwendungen (DiGAs).
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Kontakt: maximilian.schumergruber@tum.de
10.03.2026
Master’s Thesis - Conflict Detection and Resolution in Roadside-Vehicle Cooperative Perception
The Chair of Robotics, Artificial Intelligence, and Real-Time Systems offers a Master’s thesis focusing on reliability and redundancy management in cooperative perception systems.
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Kontakt: erik-leo.hass@tum.de
10.03.2026
Master’s Thesis - Time and Spatial Synchronization for ETSI CAM/CPM Cooperative Perception Systems
The Chair of Robotics, Artificial Intelligence, and Real-Time Systems offers a Master’s thesis on synchronization challenges in V2X cooperative perception systems based on ETSI CAM and CPM communication standards.
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Kontakt: erik-leo.hass@tum.de
09.03.2026
AI-Based Uncertainty-Aware Cooperative Perception using Dempster-Shafer Theory for Roadside-Vehicle Sensor Fusion
Develop AI-based cooperative perception that fuses roadside and vehicle sensor data using uncertainty modeling and Dempster–Shafer Theory to detect conflicts, handle occlusions, and improve multi-sensor object tracking reliability.
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Kontakt: erik-leo.hass@tum.de
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