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21.03.2026
Professuren:
Professorin oder Professor (w/m/d) für » Carbon Composites «
An der Technischen Universität München (TUM) ist die Position als Professorin oder Professor (w/m/d) für » Carbon Composites « in Besoldungsgruppe W3 Associate/Full Professor zum Wintersemester 2026/2027 zu besetzen.
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Kontakt: faculty-recruitment@ed.tum.de
20.03.2026
Diplomarbeiten, Bachelor- und Masterarbeiten:
Master thesis: Adjoint Methods for Nonlinear Dynamic Problems: Expanded vs. Non-Expanded Formulation
Master’s Thesis: Adjoint Methods for Nonlinear Dynamic Problems: Expanded vs. Non-Expanded Formulations Background and Motivation: Objective: Tasks: Qualifications: Supervisors: References:
Inverse problems in nonlinear structural and cardiac mechanics require efficient and accurate gradient computations. For time-dependent problems, adjoint methods become challenging due to the path dependence introduced by time integration schemes such as generalized-α.
A common approach in the literature expands the system by including time-integration variables, leading to a larger coupled system (≈ 3× number of degrees of freedom) [1,2]. While this avoids complex recursive derivatives, it requires specialized solvers and preconditioning strategies.
An alternative approach avoids this expansion by analytically resolving the recursion and keeping the problem size unchanged. The relative advantages of these two fundamentally different strategies are currently not well understood.
The objective of this thesis is to implement and analyze the expanded adjoint formulation for nonlinear dynamic problems based on generalized-α time integration, and to systematically compare it with an existing non-expanded (same-size) adjoint approach already developed within the research group. Building on the group’s prior work and available implementation of the non-expanded method, the student will focus on implementing the expanded formulation from the literature, optimizing both approaches where necessary, and evaluating their performance in terms of accuracy, computational efficiency, numerical robustness, and solver and preconditioning requirements. Although the topic is methodologically challenging, the work will be closely supervised and supported.
Prof. Dr.-Ing. Michael Gee; Tahar Arjoune, M.Sc.
[1] Alberdi R, Zhang G, Li L et al (2018) A unified framework for nonlinear path-dependent sensitivity analysis in topology optimization. Int J Numer Meth Eng 115(1):1–56.
[2] Arjoune, T., Bilas, C., Meierhofer, C. et al. Inverse analysis of patient-specific parameters of a 3D–0D closed-loop cardiovascular model with an exemplary application to an adult tetralogy of Fallot case. Biomech Model Mechanobiol 24, 2039–2068 (2025).
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Kontakt: tahar.arjoune@tum.de
20.03.2026
Student assistants, internships, student research projects:
Studentische Hilfskraft im Bereich Patente & Lizenzen
Das Hochschulreferat für Forschungsförderung und Technologietransfer (TUM ForTe) sucht zum nächstmöglichen Zeitpunkt zur Unterstützung des Bereichs Patente und Lizenzen motivierte und engagierte studentische Hilfskräfte (m/w/d). 10-20 Std./Woche bei freier Zeiteinteilung.
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Kontakt: Agne.Makris@tum.de
20.03.2026
Internal job board at TU Munich:
Assistenz für Sekretariat (m/w/d) zur Aufstockung 8 Std./Wo für die Professur Photogrammetrie und Fernerkundung
Wir suchen zum nächstmöglichen Zeitpunkt eine Teamassistenz für 8 Std./Wo, die unser Sekretariat für die Professur von Photogrammetrie und Fernerkundung am TUM Innenstadt-Campus in München unterstützt.
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Kontakt: susanne.oxe@tum.de
20.03.2026
Diplomarbeiten, Bachelor- und Masterarbeiten:
Master Thesis - Surgical Scene Understanding using VLM
Modern computer-assisted surgery relies increasingly on robust visual understanding of the operating room. While most existing approaches for surgical scene understanding and phase recognition are based on narrow-field-of-view endoscopic or monocular camera data, real-world operating rooms often provide significantly richer visual contexts.
This thesis aims to investigate surgical scene understanding using multiple images for surgical phase recognition, and higher-level scene representations such as surgical scene graphs. The goal is to analyze how VLM/multi-view VLMs can use the visual context can improve robustness, generalization, and interpretability.
The project will commence with a comprehensive review of the state-of-the-art in surgical activity recognition, surgical phase classification, and scene graph–based modeling. Based on this review, existing methods will be categorized and experimentally evaluated, with adaptations made where necessary to support panoramic or wide-field-of-view imagery. Particular emphasis will be placed on testing and validating approaches on recordings beyond classic benchmark datasets, including less constrained or previously unseen surgical recordings.
The student is encouraged to bring in their own ideas and creativity. The outlined approach serves as a guiding framework rather than a strict implementation plan.
Your own creativity is welcome to solve the problem; the upper proposal merely presents an idea.
Please read the application details: https://hex-lab.io/vacancies/01_students/
Key research areas include:
Reviewing the state-of-the-art in surgical activity / phase classification techniques and surgical scene graph techniques
Categorize and experiment with existing approaches
Test on recordings aside from classic datasets
Recommended background (or motivation in learning):
Basic knowledge of computer vision
Experience with deep learning model training and application
Some experience with C++ and Python
Medical Context:
- https://github.com/egeozsoy/ORacle
Multi-View VLMs:
- InternVL https://github.com/OpenGVLab/InternVL
- LLaVA-NeXT as well: https://arxiv.org/abs/2407.07895; https://github.com/LLaVA-VL/LLaVA-NeXT
Fine-tuning VLMs for 3D vision tasks:
- https://github.com/openvla/openvla
- https://roboflamingo.github.io/
- https://physx-anything.github.io/
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Kontakt: hannah.schieber@tum.de
20.03.2026
Nachrichten der Verwaltung:
Abgabe von Geräten / "TUM-Basar" u. "eGon"
"TUM-Basar" / Abgabe von Geräten TU-intern sowie aktuelle Angebote aus dem Bayerischen Behördennetz "eGon" (entbehrliche Gegenstände online). Weiterverwendung nicht mehr benötigter Einrichtungsgegenstände, Maschinen und Geräte, wobei die Funktionsfähigkeit der Anlagen gewährleistet sein soll.
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Kontakt: München und Garching: Frau Binder, Tel. 089/289-25558, E-Mail: jul.binder@tum.de; Weihenstephan: Frau König, Tel. 08161 71-3211, sandra.koenig@tum.de
19.03.2026
Non-academic staff:
Administrative & Project Support (m/w/d; Freelance / Honorarbasis)
TikTalks is an interdisciplinary research project examining how TikTok’s algorithmic recommendation system shapes personalized feeds and user experiences. We are seeking a freelance team member to support the project’s administrative and organizational core. The role focuses on structured execution, precision, and reliable coordination across project management, event organization, and administrative processes.
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Kontakt: sobieska@responsibletechhub.com
19.03.2026
Academic staff :
Research Assistant (PhD candidate) (m/f/d) with a focus on “Robotic additive manufacturing of wood–mycelium habitat structures for urban biodiversity”
Urban environments offer vast, yet underused, potential for biodiversity. The ROBOHAB project combines ecology, fungal biotechnology, computational design, and robotic additive manufacturing to develop 3D‑printed wood–mycelium habitat structures that mimic the ecological functions of natural deadwood.
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Kontakt: benz@hfm.tum.de; wolfgang.weisser@tum.de
19.03.2026
Non-academic staff:
Assistenz Prüfungs- und Studiengangsverwaltung (m/w/d)
Zur Verstärkung unseres Teams suchen wir ab sofort am Standort München eine
Assistenz Prüfungs- und Studiengangsverwaltung (m/w/d).
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Kontakt: hedi.schmid@hfp.tum.de
19.03.2026
Academic staff :
Postdoctoral Researcher (m/f/d, 50–100%) – Sustainable Entrepreneurship & Energy – TUM, Professorship of Corporate Sustainability - Brewery and Food Industry Management (Prof. Belz)
Postdoctoral position (50–100%) at TUM in the field of sustainable entrepreneurship and energy. Research on the scaling and impact of sustainable enterprises in the Global South. Embedded in international networks (TUM SEED Center & TUM ENERGISE Centre). Start: June 2026.
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Kontakt: annette.tischler@tum.de, seed-center@tum.de
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