1,608 engineering-computation "https:" "https:" "https:" "https:" "https:" "University of Cambridge" positions at Nature Careers
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Associate or Senior Editor, BMC Digital Health, BMC Artificial Intelligence, BMC Biomedical Engineer
within relevant fields. Experience, Skills & Qualifications: Essential Educated to PhD or MD level (or equivalent) in artificial intelligence, computer science, biomedical engineering, digital health, data
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, gene editing, medicinal chemistry, and DNA-encoded library (DEL) technology, among others. For detailed information, please visit us at https://siais.shanghaitech.edu.cn/ . Join Our Institute: Faculty
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Title: Associate or Senior Editor, Nature Reviews Computing Location: Shanghai, Madrid or Pune - hybrid working model Closing date: April 15th, 2026 About Springer Nature Springer Nature is one
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knowledge transfer. Discipline, including, but not limited to: Electronic and Information Engineering, Computer and Data Engineering, Electronic and Electrical Engineering, Information Engineering
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and knowledge transfer. Discipline, including, but not limited to: Electronic and Information Engineering, Computer and Data Engineering, Electronic and Electrical Engineering, Information Engineering
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The Air Force Science & Technology Fellowship Program (AF STFP) provides nationally competitive fellowship awards for postdoctoral and senior scientists. Selected individuals have the unique
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, Materials Science, Energy Science, Energy Engineering, Optics, Computer Engineering, Integrated Circuits, Information Engineering, Robotics, Network Science, Artificial Intelligence, Financial Engineering
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Therapy AI Synthetic Biology Metabolic Engineering Multi-Organ Connected Microphysiological System Faculty of Computer Science and Artificial Intelligence Department of Computer Science and Engineering
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a leading research institute focused on understanding cancer biology and developing innovative therapies. Our Bioinformatics & AI Expertise Unit provides advanced computational support to multiple
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. The candidate will lead computational analyses of these datasets, using the laboratory’s suite of existing AI/ML tools to assign structures to unidentified peaks in metabolomic datasets (e.g., https