Research Assistant with the possibility for PhD – Interdisciplinary research in Electric Discharge Machining assisted by AI / ML

In der aktuellen Covid-19 Situation laufen die Rekrutierungen weiter. Es kann dabei allerdings zu Verzögerungen kommen. Vielen Dank für Ihr Verständnis.

100%, Zurich, fixed-term

The Institute of Machine Tools and Manufacturing (IWF) at ETH Zurich focuses on fundamental and applied research in many areas of production engineering. Headed by Prof. Dr. Konrad Wegener, the fields of activity range from production machines, manufacturing processes and machine simulation to virtual reality. The IWF works in close cooperation with inspire AG, the leading Swiss competence centre for technology transfer to the mechanical, electrical and metal industries and many other industry partners. To strengthen our process group we offer the following position for young scientists (m/f).

Project background

Electric discharge machining is one of the most important process technologies for the production of tools, moulds and dies, and enables efficient mass production. Hardly any device of daily life can do without this technology today. Due to the extreme process conditions, temperatures above 10000 K, high spatial and temporal derivations, multiple phase (dielectric, plasma and melt) the understanding of the processes, which is the basis for process improvement, is still limited. At the IWF, this interesting process has been researched for years and new results are constantly being obtained that are helpful for process optimisation. Neither metrological nor numerical simulations alone are sufficient to understand and describe electrical discharge machining. For a better understanding of the process, physical simulation, experimental work and new artificial intelligence (AI) and machine learning algorithms must be combined sensibly. State-of-the-art experimental machines, powerful measurement and simulation technology are available at the IWF and are to be further developed.   

Job description

In order to optimize the grinding process, a new generation expert system is to be developed. With the help of artificial intelligence (AI), machine learning (ML) and data analytics on top of physics based modelling, practice-relevant efficient machining strategies can be developed based on a physically based process model.

Your profile

You have a Master's or diploma degree in mechanical engineering, material science, electrical engineering, or physics. You are highly motivated and eager to learn. In addition, you like to combine theoretical considerations and models with experimental tasks and would like to be involved in teaching at the IWF. Accurate work and very good communication skills in German and English round off your profile. We offer you a full-time position for the duration of your doctoral studies. Through close cooperation with our project partners you will quickly establish contacts with the Swiss industry. In our young team you will work at the cutting edge of today's knowledge in production and manufacturing technology.

ETH Zurich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

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