Search for public opportunitiesRegister now and browse all open positions. It's free!Profit from a great search interface and directly apply to the position of your choice. SiROP - Excellence in Science! Profit from a great search interface and directly apply to the position of your choice. SiROP - Excellence in Science! Notify me when new projects of my interest are advertized!You define what you are interested in and we will send you an Email when a new project matches your criteria, it's that easy. You define what you are interested in and we will send you an Email when a new project matches your criteria, it's that easy. Results |
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Semantic segmentation augments visual information from cameras or geometric information from LiDARs by classifying what objects are present in a scene. Fusing this semantic information with visual or geometric sensor data can improve the odometry estimate of a robot moving through the scene. Uni-modal semantic odometry approaches using camera images or LiDAR point clouds have been shown to outperform traditional single-sensor approaches. However, multi-sensor odometry approaches typically provide more robust estimation in degenerate environments. - Computer Vision, Image Processing, Intelligent Robotics, Signal Processing
- Master Thesis, Semester Project
| This project aims to investigate the use of GNNs for cascading failure analysis in power grids. The primary goal is to evaluate various GNN architectures and, if possible, develop new models tailored to the task. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| Use evolutionary algorithms with analytical force closure metrics to learn the optimal morphology of a dexterous hand. - Intelligent Robotics
- Master Thesis, Semester Project
| Develop a method for collision aware reaching tasks using reinforcement learning and shape encodings of the environment - Intelligent Robotics
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| CFD-based analysis of aerodynamic and thermal loads on the surface of space launcher and design of methodology suitable to predict CFD loads. - Aerospace Engineering, Mechanical and Industrial Engineering
- Semester Project
| Generative Pre-trained Transformers have enabled an unprecedented level of performance in
Natural Language Processing tasks via Large Language Models (LLMs). Yet, a major aspect
that is hindering their use in critical applications is their lack of reliability. Hence, one approach
to address this question is through the lens of uncertainty quantification.
Nonetheless, current work either requires the retraining of the models, which is not
suitable for LLMs, or incur a high computational cost. To cope with that, the goal
of this project is to leverage recently proposed probes for LLMs for tractable Bayesian
learning and uncertainty quantification for various downstream tasks. - Mathematical Sciences
- Master Thesis
| Develop zero-shot scene graph alignment algorithm using multi-modal data such as point clouds, CAD meshes, etc. - Computer Vision
- Master Thesis, Semester Project
| SwissFEL is one of only five hard X-ray FEL user facilities worldwide, and allows the observation of matter on the spatial and time scales of atomic processes. Many graphical high-level applications (HLA), employed regularly for the machine setup, require the operator to manually perform a number of steps before and after the they are used. To automate these steps and unify the concept across different HLA, you will develop a Python library to interface the corresponding hardware controls. You will also implement and test the concept for the bunch length measurement tool. - Engineering and Technology, Physics
- Internship
| Laser cladding (LC) and high-speed laser cladding (HSLC) are direct metal deposition (DMD) techniques where metal powder is delivered to a substrate using a carrier gas, and a laser melts the powder and substrate to create a coating. The primary difference between LC and HSLC lies in the powder-laser interaction, as shown in Figure 1. In LC, the powder is injected into a molten pool on the substrate, while in HSLC, the powder is melted in flight before reaching the substrate. This distinction allows HSLC to achieve deposition speeds up to two orders of magnitude higher than LC while reducing the heat input to the substrate. Achieving these benefits, however, depends on the efficient and predictable interaction between the powder and the laser beam.
This project investigates the behavior of powder streams in HSLC using a dual approach: advanced numerical simulations and experimental validations. It explores the influence of key input parameters, such as gas flow settings, nozzle geometry, and material properties, on powder stream dynamics. By combining numerical modeling and experimental analysis, the study aims to uncover new insights into powder stream behaviors, optimize the process, and refine the robustness of the model under diverse conditions.
- Manufacturing Engineering
- Bachelor Thesis, Master Thesis, Semester Project
| Whereas optimizing a wing for minimum drag in given operating conditions is relatively easy, the assessment of the effects of the geometry modifications in extreme conditions (gust response) is essential. In practice, the aeroelastic response of a wing shall be implemented (low order is acceptable) and the physics associated with gust response shall be characterized. - Aerospace Engineering, Mechanical and Industrial Engineering
- Master Thesis, Semester Project
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