Research assistant with possibility for PhD: Improving stability predictions in milling through machine learning
The Institute of Machine Tools and Manufacturing (IWF) performs international leading research on machine tools and in the field of production engineering. For a new research project with close industrial contact we are looking for a new PhD candidate.
Project background
Process instability, resulting in chatter vibrations, remains the main limiting factor for modern CNC milling processes. These vibrations can lead to low surface quality, tool breakage and, in extreme cases, even to machine failure. Typically, unstable process conditions are avoided by creating stability lobe diagrams, which indicate stable cutting depths as a function of the spindle speed. However, existing models provide inaccurate results, making their usage unattractive for real industrial application cases. One alternative solution is to build experience-based stability lobe diagrams from measured stable and unstable cutting conditions. While it is straight-forward to autonomously and continuously monitor the milling process, making stability predictions from experimental observations requires an enormous amount of data, which is not practicable for industrial use. It is hence targeted to develop a hybrid approach, which combines the existing knowledge about the milling process and the capabilities of machine learning approaches. With the continuously growing database, it is expected that the prediction accuracy improves significantly over time.
Job description
You will be participating in this research project will work at the interface of mechanical engineering and machine learning to improve prediction quality of stability models. The work will be performed in close collaboration with leading Swiss industry partners and involves a mix of programming, modelling and experimental validation. You can expect a full-time position in a highly motivated, young research group that offers an excellent research infrastructure. The work place is located in the heart of Zurich. There is the possibility to transition from the research assistant position to a PhD position.
Your profile
We are looking for someone with a Master’s degree (or close to completion) in Mechanical Engineering or a similar field from a recognized university with an excellent GPA, strong analytical skills and some experience in machine learning. A background in machine tool vibrations is beneficial. Good programming skills in Python are required. Furthermore, proficient oral and written English skills are expected.
ETH Zurich
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Interested?
We look forward to receiving your online application including:
- motivation letter
- a full CV
- and transcripts of all degrees obtained (in English)
Please note that we only accept applications submitted through our online application portal. Applications via email or postal services will not be considered. Please do not hesitate to contact Dr. Michal Kuffa at kuffa@iwf.mavt.ethz.ch for any inquiries about the position (no applications).
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