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technologies promise to revolutionize multiple branches of science by solving problems that cannot be tackled by classical systems. While efficient and large-scale quantum computers are still far from being
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or graduate degree is preferred. Minimum of 12 years of experience in clinical development, with exposure to multiple clinical operations functions. Proven experience in field-based, site-facing clinical
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, or a related field Programming experience (e.g., Matlab, Python) Experience with at least one electrophysiological recording method or related experimental method listed above The ability to design and
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among research groups Establishing mechanisms to gather input, needs, and feedback from community members Managing the ETH Zurich side of the Joint Doctoral Program on Learning Sciences (JDPLS ), and
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. Opportunities to engage in cutting-edge research with the potential for high impact in multiple fields and a chance to contribute meaningfully to an ambitious research agenda focused on creating positive impacts
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interested in current political and societal discussions Be able to work independently, manage multiple tasks and deadlines Be a team player with strong communication skills Have experience with coding (e.g
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. Within this field, we are continuously developing and adopting various algorithms for multiple applications such as automating quality control, detecting process deviations and finally predicting
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. This position is part of a collaborative project funded by the Swiss National Science Foundation, which supports multiple researchers, at ETH Zurich and at partner universities, and focuses on the development
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the framework of a large National Competence Center of Research (NCCR) “Antiresist” (for more information, view ) involving clinicians, academic and industrial research partners across multiple disciplines, a
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located in the SLA building on the Schwerzenbach Campus of ETH Zurich, a world-leading institute. We provide a cutting-edge work environment, multiple well-equipped facilities with expert staff, supportive