23.03.2026

Hauhechel-Bläuling

Diplomarbeiten, Bachelor- und Masterarbeiten:
Tagfalter-Pflanzen Interaktionen auf Blühstreifen im Agrarland   

Blühflächen sind wichtige Habitate zur ökologischen Aufwertung von Agrarlandschaften. Ziel der ausgeschriebenen Arbeit ist, die Auswirkung unterschiedlicher Saatmischungen und Mahdregime auf die vorkommenden Tagfalterarten zu erfassen. Mit Hilfe der jeweils blühenden Pflanzenarten und auf den Flächen vorkommenden Futterpflanzen für Raupen können weitere Rückschlüsse gezogen werden.

Kontakt: franziska.mueck@tum.de

23.03.2026

Student assistants, internships, student research projects:
Student assistant (m/f/d) - professorship for Wood technology   

Starting immediately, we are looking for student assistants (all genders) to support our research projects in the field of wood technology. Working hours: 8–15 hours per week with flexible scheduling.
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Kontakt: kovryga@hfm.tum.de

23.03.2026

Diplomarbeiten, Bachelor- und Masterarbeiten:
Master’s Thesis: Leveraging iPhone ARKit Pose Estimation for Visual SLAM and Scene Understanding   

This thesis aims to investigate how Apple’s ARKit pose estimation system can be used, analyzed, and potentially extended for computer vision and robotics-related applications. The work will evaluate ARKit’s accuracy, robustness, and suitability as a replacement or complement to traditional Visual SLAM pipelines.
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Kontakt: tim.schreiter@tum.de

23.03.2026

Diplomarbeiten, Bachelor- und Masterarbeiten:
Master’s Thesis: 3D Eagle Eye Visualization Using Mobile LiDAR and mobile video data   

This thesis focuses on using mobile LiDAR and mobile video to generate a real-time 3D eagle-eye visualization, enabling users to view their surroundings from a top-down perspective.
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Kontakt: tim.schreiter@tum.de

23.03.2026

Diplomarbeiten, Bachelor- und Masterarbeiten:
Master’s Thesis: Applying SAM3 for Object Classification and Tracking in Mobile Visual Data   

This thesis explores the application of SAM3 to mobile video data for object classification and tracking. The focus is on evaluating SAM3’s performance, adaptability, and limitations in real-world mobile scenarios such as dynamic scenes, occlusions, and changing viewpoints.
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Kontakt: tim.schreiter@tum.de

23.03.2026

Diplomarbeiten, Bachelor- und Masterarbeiten:
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

Diplomarbeiten, Bachelor- und Masterarbeiten:
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

Diplomarbeiten, Bachelor- und Masterarbeiten:
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

23.03.2026

Non-academic staff:
Techniker/ -in (m/w/d)   

Gestalten Sie gemeinsam mit uns exzellente Rahmenbedingungen für Forschung, Studium und Lehre an der TUM School of Computation, Information and Technology (CIT). Die TUM School of CIT ist ein wichtiger Teil der Technischen Universität München – einer der führenden europäischen Universitäten mit rund 51.950 Studierenden und mehr als 12.600 Beschäftigten.
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Kontakt: Sylwia Fournier jobs@cit.tum.de