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Field
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Fellowship and Basic Research Lab Fellowship. This position offers a unique opportunity to conduct cutting-edge research in Quantum Computing, Quantum Algorithm, and Numerical Simulation. This position, led by
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algorithm design and development of effective computing techniques To see examples of our innovative work please visit: https://www.ecshowcase.com/ What We're Looking For Education and Experience Needed
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! We
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), Machine Learning on Quantum Computers, Security of Quantum Circuits, Design Automation and Tools for Quantum Circuits, Robust and Efficient Mapping of Quantum Algorithms on Quantum Machines, Quantum Noise
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, commensurate with education and experience. Minimum Requirements: PhD in related field of study; Prior experience in computational research/developing mathematical algorithms. Preferred Qualifications: Special
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100%, Zurich, fixed-term The Distributed Computing (DISCO) Group is a research group at ETH Zurich, led by Prof. Dr. Roger Wattenhofer . We are interested in a variety of research topics on new and
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computational methods such as machine learning (ML), natural language processing (NLP), multi-modal large language model algorithms (LLMs), network analysis, and/or data mining to study the influence of digital
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bioinformatician to work on omics data. Project background The Laboratory of Regenerative and Muscle Biology (RMB), headed by Prof. Ori Bar-Nur, is a multidisciplinary and collaborative group of scientists focused
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” research group, led by Prof. Norbert Schuch. Our research lies at the interface of Quantum Information and Computation with the study of Complex Quantum Many-Body Systems. For this, we apply a combination of
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objective is to develop a next generation of AI approaches that are more sustainable and accessible. Relevant domains include mathematical and computational optimization, learning algorithms, statistical