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INSAIT - The Institute for Computer Science, Artificial Intelligence, and Technology, INSAIT Position ID: INSAIT -INSAIT -POSTDOC [#28768] Position Title: Position Type: Postdoctoral Position
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. You'll work at the exciting intersection of experimental materials science and materials informatics, collaborating with CSEM and EPFL in a Swiss National Science Foundation (SNF) Bridge Project. Your
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Your profile Candidates should have an exceptional academic record and a robust mathematical foundation. They should have published works at the main conferences in the field of machine learning, such as ICML, NeurIPS, ICLR, etc. Excellent communication skills and fluency in English (spoken and...
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studies, science and technology studies, digital humanities, computer science, literary studies, philology, cultural studies, history and philosophy of science and technology, information studies, or other
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analytics projects Mentor graduate students and supervise research activities Required Qualifications PhD in Computer Science, Data Science, or related fields Strong background in blockchain data collection
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Qualifications PhD in Computer Science, Software Engineering, FinTech Strong programming skills in Solidity and other smart contract languages Experience with blockchain platforms and development tools Proven
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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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design and structures. Profile We are looking for excellent applicants with a Doctoral degree in Mechanical Engineering, Computer Science, Applied Mathematics, or a related area of study, who are motivated
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apply for third party funding. Contributions to teaching within the Engineering Geology group are also expected. Profile PhD in Data Science, Computer Science, Mechatronics, Remote Sensing, Engineering
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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