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collaboration with the National Research Foundation (NRF) to do interdisciplinary research on pressing problems. The centre currently runs several research programmes with the Future Cities Laboratory Global (FCL
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directly atop the CMOS chips. Job description Therefore, it will be necessary to develop technologies and methods to minimize or avoid light-induced artifacts on the HD-MEAs, to establish and program a setup
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collaboration with the National Research Foundation (NRF) to do interdisciplinary research on pressing problems. The centre currently runs several research programmes with the Future Cities Laboratory (FCL) as
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should show interest in the topics of the research program. The preferred candidate has demonstrated her or his potential to conduct high-quality research, ideally by having some papers under revision
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programmes: Future Cities Laboratory, Future Resilient Systems, and Future Health Technologies. The centre provides a multicultural and interdisciplinary environment to researchers working on diverse themes
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the field of Computer Science or similar Solid background in the foundations of reinforcement learning Proven research experience with first-authored publications at peer-reviewed conferences (ICML
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candidate with a strong background geology/geomorphology, or a related discipline, a strong interest for evolutionary biology, and who is interested in bridging field data, computational modeling, and large
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100%, Zurich, fixed-term The Robotic Materials group is looking for a highly motivated postdoc for the topic of soft optical sensory skin. The Robotic Materials group headed by Prof. Hedan Bai at Department of Materials was established in October 2023. We are an international and...
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ETH Zurich, Mathematics Position ID: 1118 -POSTDOC [#25919] Position Title: Position Type: Postdoctoral Position Location: Zurich, Zurich 8092, Switzerland [map ] Appl Deadline: 2024/12/15 11:59PM (finished posted 2024/11/21) Position Description: Apply Position Description The research group...
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PhD in Computational Materials Physics or a related area is required. Experience with electronic structure calculations is essential. Familiarity with the use of machine-learning tools in materials