92 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation" "U.S" uni jobs at ETH Zurich in Switzerland
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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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language processing, algorithmic learning, fault-tolerance, blockchains, consensus, cryptocurrencies, digital money, central bank digital currency, decentralized finance, financial networks, e-democracy, voting, social
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resettlement. The position is part of an innovative project using machine learning and matching algorithms to improve the resettlement process for refugees and asylum seekers. We are developing GeoMatch , a
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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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regional geology, sourced from multiple academic institutions. Through such coordinated collaboration, SA3D aims to deliver an accurate and reliable underground geological models. To complete the SA3D
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research agenda to develop safe and effective measures to curb harmful online content and strengthen public discourse. As part of our efforts, we are using state-of-the-art machine learning techniques and
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, processing, and interpretation of satellite and drone data, as well as (2) the development of operational applications for emerging intelligent earth observation technologies. Our team develops cutting-edge
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scientific questions or develop algorithms that perform automatically some challenging tasks. This typically involves exchanging actively with collaborators and domain experts to understand the precise
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80%-100%, Zurich, fixed-term About Tethys Robotics We are a Startup located in the center of Zürich that builds underwater drones. Our field of expertise is the development of highly integrated
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datasets that include over 11,000 tree species annotations from across Switzerland, along with climatic, topographic, and lidar data. Test the best algorithm developed for the identification of tree species