EPFL - Ecole Polytechnique Fédérale de LausanneAcronym | EPFL | Homepage | http://www.epfl.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Current organization | EPFL - Ecole Polytechnique Fédérale de Lausanne | Child organizations | |
Open OpportunitiesSince the COVID pandemic it is well-acknowledged that airborne respiratory viruses significantly contribute to disease transmission. Nevertheless, our current understanding of the physicochemical processes that affect the infectivity of respiratory viruses in the aerosol and the susceptibility of the next host to airborne infection are limited. In this multi-collaborator project we will investigate the influence of air composition on the transmissibility of airborne viruses.
- Environmental Sciences, Microbiology
- PhD Placement
| The student will work on the topic of Multimodal Out-of-Distribution (OOD) Detection. The goal of this project is to explore the rich information in Foundation Models to improve the OOD Detection performances. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| The project aims to develop computational models and physical experimentation methods to understand and predict the behavior of partially damaged steel members, enabling their reliable reuse rather than recycling. By creating a framework incorporating physics-informed deep learning methods, this prject aims to facilitate the incorporation of salvaged steel into future building designs, contributing significantly to a circular economy. - Artificial Intelligence and Signal and Image Processing, Civil Engineering
- Master Thesis
| The thesis will address methodological gaps to achieve effective and safety-critical RL-based optimal control.
The project will include:
1. Reviewing existing RL approaches for continuous state-action spaces.
2. Developing ideas to tackle the challenges of optimal control systems with stability guarantees.
3. Python implementation of these algorithms in simulated physical environments, with varying degrees of complexity based on the student's computer science background.
This project offers a unique opportunity to enhance your knowledge and skills in machine learning, control theory, and optimization. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis
| Denoising Diffusion Probabilistic Models (DDPMs) are a highly popular class of deep generative models that have been successfully applied to various problems, including image and video generation. Recently, there have been attempts to apply these models to time-series data. However, they are not enough for modeling spatial-temporal interactions. They primarily focus on temporal dependencies within individual sensors, neglecting the spatial correlations between different nodes. In reality, objects are spatially correlated with each other. This project aims to explore a graph-based denoising diffusion probabilistic model to jointly capture both temporal dependencies and spatial interactions. - Artificial Intelligence and Signal and Image Processing, Civil Engineering, Communications Technologies, Electrical and Electronic Engineering, Environmental Engineering, Interdisciplinary Engineering
- Master Thesis, Semester Project
| This project is part of a collaboration between the IMOS lab and Matterhorn Gotthard Bahn, a railway company operating in the Swiss Alps. The student will work on developing computer vision algorithms for automated visual inspection of retaining walls around railway tracks. Retaining (or supporting) walls are crucial infrastructure elements responsible for maintaining the structural integrity of terrains around railway tracks and ensure safe operation. They are subject to wear and damages including cracks, concrete cancer (i.e., alkali–silica reaction), displacements, erosion and water infiltration. Images of retaining walls have already been collected and labels are available. The goal will be to design algorithms to estimate the condition of a wall, with a focus on robustness, transfer learning, and explainability (XAI). - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| This project seeks to merge the capabilities of thermal imaging with modern 3D reconstruction technologies, potentially unlock new possibilities for academic research and practical applications in urban planning, construction, and security. - Computer Vision
- Master Thesis, Semester Project
| Many graphs in real-world applications are text-attributed graphs (TAG). Examples include the description of the condition of sensors and pipes and the water distribution network over the junctions, the posts on a social media platform and the following graph over the users, the text of academic articles and the citation network over these articles, among others. This project focuses on combining the power of graph neural networks (GNNs) and large language models (LLMs) to extract information from both the text modality and the graph modality to facilitate learning on TAGs in engineering applications. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| The project is a collaboration between EPFL IMOS Lab and Belimo exploring Deep Learning algorithms for commissioning parameters of Heating, Ventilation, and Air Conditioning systems - Engineering and Technology
- Master Thesis
| Researchers have started to explore data-driven physics simulations, particularly with Graph Neural Networks for rigid objects collisions. However, simulating rigid collisions among arbitrary shapes is notoriously difficult due to complex geometry and the strong non-linearity of the interactions. In this project, you will focus on the task of learning/simulating rigid objects dynamics with Graph
Neural Networks (GNNs), with the end-goal of predicting future or alternative trajectories for physical rigid objects in a scene. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
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