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Studentische Hilfskräfte, Praktikantenstellen, Studienarbeiten
06.05.2024
Search for volunteers for the GfÖ conference (6-13 sept)
Kontakt: mar.vergara.martin@tum.de
02.05.2024
Development of Computer Vision module for environment perception and motion planning (Hiwi, Research Internship)
Vision is a core component of today’s autonomous robots systems, enabling the robot to have a perception of the environment and interact with it. The main focus of this work is to create the vision pipeline for an assistive-robotics platform that will enable people with disabilities to perform activities of daily living.
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Kontakt: Dipl.-Ing. Ioannis Xygonakis ioannis.xygonakis@tum.de -- Riddhiman Laha riddhiman.laha@tum.de
02.05.2024
BCI-Gym: Development of Virtual Environments for Brain-Computer Interface users training (Hiwi, Research Internship)
The potential for invasive Brain Computer Interface (iBCI) systems to dramatically improve the livelihoods of those who have lost motor functionality has increased in recent years. This improvement has emerged due in part to advances in the field of deep learning, but the performance of these models varies significantly depending on the quality of the data collection and the design of the experiment. For iBCI participants who have lost the ability to move, the decoding models will be attempting to decode imagined movement, rather than actual movement. To have the best chances at decoding imagined movement, an effective and realistic virtual environment is essential as it increases the chance that the iBCI participant effectively embodies the virtual arm, thereby allowing for synchronization between the collected neural data and the imagined arm position. This position allows the researcher to work alongside experts in neuroscience, machine learning, and robotics in a supportive and resource-rich environment.
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Kontakt: Dr. Alexander Craik - alex.craik@tum.de -- Dipl.-Ing. Ioannis Xygonakis - ioannis.xygonakis@tum.de
26.04.2024
Master Thesis: Deep Learning for Brain Tumor Modeling
We model brain tumor growth for improved radiotherapy planning based on 3D magnetic resonance images (MRI). Partial differential equation (PDE) based models have the potential to personalize glioma therapy. However, calibrating these models to individual patients is computationally expensive using traditional numerical solvers and classical optimization techniques.
First tests with simple tumor models show promising results using differentiable deep learning based solvers for fast, gradient based optimization. Thereby a neural network inputs the specific tumor parameters like growth and diffusion rate and predicts a tumor cell concentration inside the brain [1]. To calibrate this model for a specific patient, the input parameters are optimized utilizing the differentiability of the network with respect to the input.
Your role would be to utilize state-of-the-art network architectures to develop a deep learning-based solver for more realistic brain tumor growth models.
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Kontakt: j.weidner@tum.de
26.04.2024
Bachelor / Master Thesis: What was before the brain tumor? Recovering the original state of the brain for digital brain tumor twin.
Recovering the original state of the brain for digital brain tumor twins using MRI.
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Kontakt: Jonas Weidner j.weidner@tum.de
24.04.2024
IT-Werkstudenten (m/w/d) für Ubuntu Linux Deployment Projekt gesucht
ITO School of CIT sucht Werkstudenten (m/w/d) für IT-Automation Projekt (Puppet, Ansible, Ubuntu)
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Kontakt: fedorov@tum.de
22.04.2024
Web developer HiWi position for autonomous driving website
Kontakt: eivind.meyer@tum.de
17.04.2024
2D axisymmetric membrane model
Master Thesis: Modelling of next-generation MEMS microphones for hearing aids
We are looking for students who like to work in an interdisciplinary team and intend to realize their master's thesis within our group at Professorship of Microsensors and Actuators embedded in the EU project Listen2Future.
Topic
Advances in material science have enabled the use of piezoelectric materials in MEMS microphones. In contrast to commonly used capacitive MEMS microphones, piezoelectric microphones require less energy and are, therefore, useful for mobile applications such as hearing aids. Another advantage of the piezoelectric microphone is the linear relationship between electrical voltage and force. This simplifies force-feedback control of the sensor and thus opens the possibility of increasing the sensor performance even more. Crucial for this is the design of the microphone membrane. Therefore, highly accurate models must be set up to simulate the microphone behavior.
Within this Master Thesis, you will set up a shell model of the microphone membrane to obtain a complete 3D model. Currently, a 2D axisymmetric FEM model is available, which cannot cover the full 3D behavior. A shell model could simulate additional resonance modes and promising membrane designs for force-feedback control.
Simulation is done in COMSOL Multiphysics, the gold standard software to simulate the coupling of different en-ergy domains.
Work packages
• Topic familiarization and literature survey
• Familiarization with COMSOL Multiphysics
• Setting up a shell model of the piezoelectric microphone membrane
• Comparison with the existing 2D axisymmetric model
• Investigation of new membrane designs for force-feedback control
• Documentation and presentation of the results
Requirements
Background in one of the following fields:
• Electrical Engineering
• Mechanical Engineering
• Physics
• Materials Science
• Related fields of study
Timetable
The thesis can be started immediately.
Contact
Til Friebe, M.Sc.
Doctoral Candidate
Phone: +49 89 28923129
Email: til.friebe@tum.de
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Kontakt: til.friebe@tum.de
15.04.2024
Studentische / wissenschaftliche Hilfskraft (m/w/d) für Datenmanagement in der Hirnforschung
Am Neurokopfzentrum des TUM Klinikums suchen wir eine studentische / wissenschaftliche Hilfskraft für Datenmanagement in der Hirnforschung.
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Kontakt: simon.jacob@tum.de
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