Department of Civil, Environmental and Geomatic EngineeringAcronym | D-BAUG | Homepage | http://www.baug.ethz.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Parent organization | ETH Zurich | Current organization | Department of Civil, Environmental and Geomatic Engineering | Child organizations | |
Open OpportunitiesDo you want to work on smart control algorithms that control the infrastructure of a road network to optimize vehicle traffic flows? And do you want to try them out in a fully-fledged traffic simulator called SUMO? Then this is thesis project is for you.
The goal of this thesis is to develop an infrastructural control algorithm that optimizes efficiency and fairness of road traffic flows. You can choose one from the following control applications: intersection management (control flow at intersection), ramp metering (control flow that enters highways), perimeter control (control flows between cells/regions of an urban network).
Optional, if interested: depending on your progress and results, we can also support & guide you with creating a scientific publication for your first steps into academia. - Control Engineering, Road and Rail Transportation, Simulation and Modelling, Systems Theory and Control
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis
| A masonry bridge is a type of bridge constructed using masonry, which includes materials such as stone, brick, or concrete blocks. These bridges rely on the principles of compressive strength, where the weight and loads are transferred through the structure primarily by compressing the masonry materials. Many masonry bridges are designed with arches, which effectively distribute weight and handle compressive forces. Structural health monitoring (SHM) is of great significance in maintaining the safe operation of such infrastructure as its material properties are deteriorating due to effects such as climate change, while the demands of modern transport systems are increasing significantly. - Structural Engineering
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| Time-series data is increasingly prevalent across various domains, including finance, healthcare, and environmental monitoring. The ability to extract meaningful information from time-series data is crucial for prediction, classification, and anomaly detection. This project focuses on exploring different time-series representations and their impact on machine learning tasks. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| A machine learning-based classifier will be developed to automatically detect abnormal GNSS ephemerides in daily broadcast ephemeris files. - Earth Sciences
- ETH Zurich (ETHZ), Semester Project
| A dynamic tropospheric process noise model will be implemented into GNSS real time kinematic (RTK) algorithms to improve the estimation of drone-based GNSS zenith total delays (ZTDs). - Earth Sciences
- ETH Zurich (ETHZ), Semester Project
| This thesis explores ionospheric modeling using GNSS and potentially VLBI data, employing Gaussian Process regression to address the non-linear behaviors and noise inherent in such data. The study focuses on enhancing predictive accuracy and the quantification of uncertainties in ionospheric variations, which are essential for improving global navigation and communication systems. - Earth Sciences
- Bachelor Thesis, ETH Zurich (ETHZ)
| This master thesis aims to improve the retrieval of soil moisture using the GNSS Interferometric Reflectometry (GNSS-IR) method by the development of a new, machine-learning based model for the correction the vegetation influence on the retrieval. - Earth Sciences
- ETH Zurich (ETHZ), Master Thesis
| This master thesis aims to explore the application of Physics-Informed Neural Networks (PINNs) to regional geoid modeling. PINNs integrate physical constraints into neural network architectures, offering a novel approach to accurate geoid modeling while maintaining interpretability. - Earth Sciences
- ETH Zurich (ETHZ), Master Thesis
| In this study, the student should apply deep learning algorithms to segment the measurements from the Surface Water and Ocean Topography satellite mission, specifically focusing on inland water bodies. The outputs of this study may contribute to inland water detection during flood events and also potentially to refining the pre-defined water body shapes. - Earth Sciences
- ETH Zurich (ETHZ), Master Thesis
| In this study, the student should develop a generative model to separate the total signals measured by GRACE(-FO) satellite missions into the contributions of individual water storage components. The results will be evaluated by comparing them with independent in-situ and satellite-based storage observations. The findings of this study will contribute to a better understanding of the terrestrial water cycle from a global perspective. - Earth Sciences
- ETH Zurich (ETHZ), Semester Project
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