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against experimental data. Proficiency in Python, together with good software engineering practices such as version control and testing, is expected. Experience with high-rate dynamics, cavitation
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maximum) Contact information for two potential referees Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will
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and transcripts of academic records or proof of anticipated completion Contact information for two potential referees Please note that we exclusively accept applications submitted through our online
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research experience Contact information for reference letters from 3 referees. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or
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experimental and simulated data, leveraging AI and machine learning techniques Contribute to novel computational optimisation methods for machining processes Develop and implement automation solutions, including
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. Further information about our Institute can be found on our website . Questions regarding the position should be directed to Ms Edita Schroeppel, email schroeppel@imsb.biol.ethz.ch (no applications). We
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. Further information about us can be found on our website . For questions about the position, please contact Myriam Dunn Cavelty at dunn@sipo.gess.ethz.ch (no application documents). About ETH Zürich ETH
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. The job description is available on the University’s website . Further information may be obtained from Prof. Niko Geldner (Niko.Geldner@unil.ch ), Director of the DBMV. Applications, in English, should
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exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. Further information about the professorship can be found on our
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question. Measured data is thoroughly analyzed with state-of-the-art theoretical models and published fully open access. The aim of our research is to advance the fundamental understanding of electrical