1,600 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of Warwick" positions at Nature Careers
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screening, and multi-omics data to uncover cancer vulnerabilities and enable next-generation therapeutic target discovery. The group is supported by major competitive funding, contributes actively
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employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by employing staff who bring unique
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. Our team is part of the Quantum Optics, Quantum Nanophysics and Quantum Information group of the Faculty of Physics. We are a member of the Vienna Center for Quantum Science and Technology (VCQ), one
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of Zurich (UZH). Questions about the application procedure / Information on your application The professorship is part of the new Responsible AI Cluster at UZH, which is part of the UZH.ai initiative
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cooperation partner for other research institutions, university hospitals, and companies. A wide range of information services for patients, children, and young people completes our portfolio. To strengthen our
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believe that better imaging leads to better outcomes for every patient. Job Summary Operates under general supervision. Performs data abstraction, collection, and entry to support clinical research
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from Physical Review Letters. Some of our works are highlighted by globally prestigious journals including Nature. More information, please refer to our website. This will be a great opportunity to join
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collaboration by proposing an original hybrid rule-driven/data driven approach to artificial intelligence and by studying efficient optimization algorithms. The team focus on robotic applications like environment
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relocation expenses. Location of work: School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, K1H 8M5. Contact information: Dr. Alain Stintzi, Director
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computational methods and algorithms for genomic sequencing data analysis, particularly in the context of genome assembly. This is an exciting opportunity to develop novel computational approaches for microbial