67 coding-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Washington University in St" uni jobs in Switzerland
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is 8 January 2026. We are not accepting applications for this job through AcademicJobsOnline.Org right now. Please apply at https://ethz.ch/en/the-eth-zurich/working-teaching-and-research/faculty
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environment where philosophy meets data science, public health, medicine, and law? At the Health Ethics & Policy Lab (https://bioethics.ethz.ch ), you will join a team committed to shaping responsible
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understanding of the aging of solid insulation under mixed-frequency medium-voltage stress, see https://doi.org/10.1088/1361-6463/acd55f for a relevant example research work of our team in this area. Profile
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of predicting electronic, structural, and thermal quantities while leveraging underlying symmetries for computational efficiency. There will be a significant computational component in deploying multi-GPU codes
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(FOPH) of Switzerland and the Centers for Disease Control and Prevention (CDC) of the United States. We value good software engineering practices. We perform code reviews, have automated testing pipelines
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of research excellence through peer-reviewed publications Evidence of comittment to reproducibity in bioinformatics through the use of Code Repositories Evidence of ability and experience in handling
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related field Solid background in physical optics, experience in interferometry and/or cryogenic optics is an asset Extensive experience with optical design and simulation tools (e.g. Zemax, Code V, FRED
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mechatronics systems is a plus Excellent coding skills in python, ROS, and RL&IL pipeline experience on simulator and training libraries. Knowledge on C++ is a plus Experience with Physics simulators such as
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programming skills (ideally Python) and commitment to clear, reproducible, well-structured code Working knowledge of SQL and/or NoSQL databases (and motivation to deepen your expertise) Strong analytical
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) Unsupervised machine learning and deep learning methods Analysis, visualization, and interpretation of learned design spaces Contributing to research outputs (prototypes, publications, open-source code) Profile