Research assistant with possibility for PhD – Optimization of Railway using Artificial Intelligence with Physical Models
Job description
A considerable portion of the noise produced by trains stems from rolling noise, primarily influenced by the roughness of both the wheel and the rail surfaces.
Accurately evaluating noise generation at the wheel-rail interface requires measuring the roughness of the rail network.
Traditional direct measurements with trolley devices require unobstructed tracks and have speed limitations. Indirect methods, like measuring axle-box accelerations, allow measurements during regular operations but only provide rough estimates of acoustic roughness.
This project explores the feasibility of a non-contact measurement approach using optical laser triangulation sensors to gauge rail roughness from moving trains.
Your profile
You have to have a master's degree preferably in Mechanical Engineering. The position is coupled with the possibility of a PhD study at ETH Zurich.
Qualified candidates should have the following capabilities :
- Experience and interest in experimental working
- Interest in railway
- Good knowledge of data analysis and signal processing
- Programming experience
- Competences in Manufacturing Technology
You are highly motivated and eager to learn. In addition, you like to combine theoretical considerations and models with experimental tasks and have valuable technical skills.
Through close cooperation with our project partners, you will quickly establish contacts with the Swiss industry. In our young teams, you will work at the forefront of today's knowledge in manufacturing.
We offer a modern working environment in a young and motivated team and an interesting topic in a fast-growing field of research.
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