263 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Newcastle-University" positions in Switzerland
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. Please submit these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/phd-position-in-data-driven
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Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
! More Do not overlook the inclusion of Academic Europe in your application. Where to apply Website https://www.academiceurope.com/ads/doctoral-candidate-in-computer-vision-and-ma… Requirements Research
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will be responsible for a range of research tasks, including literature search, data curation, coding for systematic literature reviews, data analysis, and miscellaneous administrative activities (e.g
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component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
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100%, Zurich, fixed-term The Swiss Data Science Center (SDSC) is seeking a PhD student for a Swiss National Science Foundation (SNSF) project, starting May 1st. This role sits at the intersection
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researchers and who help to shape a forward-looking university with innovative research-based teaching. Information on your application Please submit your electronic application for this position by March 8
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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi
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motivated individual to develop Python tools for analyzing data from our holographic cloud particle imagers. Our research group studies the crucial role of clouds and aerosols in the climate system, aiming
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to efficiently train on the large, densely-connected and graph-structured data encountered in our systems of interest. Your contributions would be across the spectrum from methodological development
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. The successful candidate will bridge biological, behavioral, and cultural data to understand the emergence of gendered power structures across taxa and ecological contexts. While strongly rooted in evolutionary