Research assistant with possibility for PhD: Simulation and data driven (machine learning) process optimization for hand held machine tools
100%, Zurich, fixed-term
The Institute of Machine Tools and Manufacturing (IWF) performs international leading research on machine tools and in the field of production engineering. We are looking for a new PhD candidate for a new research project with close industrial contact.
Project background
Process prediction remains the main challenge for modern handheld processes. Typically, unstable process conditions are avoided by extensive experimental study. Existing physical models provide inaccurate results, making their usage unattractive for real industrial application cases. Making 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 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 work at the interface of mechanical engineering and machine learning to improve the prediction quality of process and data models.
- The work will be performed in close collaboration with leading Swiss industry partners and involves a mix of programming, modelling and experimental validation.
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 tools is beneficial. Good programming skills in Python are required. Furthermore, proficient oral and written English skills are expected.
Your workplace
Your workplace
We offer
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.
We value diversity
Curious? So are we.
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).
About ETH Zürich
Curious? So are we.
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).