1,843 computer-science-programming-languages-"Prof"-"University-of-Strathclyde"-"Prof" positions at Nature Careers
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interdisciplinary, and together we contribute to science and society. Your role Interact with research groups in Luxembourg in the context of ELIXIR Luxembourg to consult and perform joint research Plan and conduct
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the relevant union. The position is part of DTU’s Tenure Track program. Read more about the program and the recruitment process here . You can read more about career paths at DTU here . Further information
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program contact information for at least three letters of recommendation The Chemistry Department, School of Humanities & Sciences, and Stanford University value faculty who will help foster an open and
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One tenure-track faculty position at all levels (Assistant, Associate, or Full Research Fellow) is open for a qualified individual to establish an active research program at the Institute
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Associate or Senior Editor, Nature Communications (Electrical Engineering and Energy Infrastructure)
write Editorials Experience, Skills & Qualifications: A PhD (or equivalent experience) in electrical engineering, energy infrastructure, or related areas. Experience with applied computational techniques
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in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international work environment with more than 50 nationalities
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Capability programme, which underpins long-term research of national and global importance. We are now seeking a Science Director to shape and lead the future direction of our interdisciplinary science, and to
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experimental molecular biology and cell biology is a merit, as is understanding of physics and structural biology, and experience in computational work including programming. You should be highly motivated and
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We are seeking outstanding, highly motivated, and creative candidates for a Senior Researcher or Researcher role in a new Therapeutic Genome Engineering (TGEn) group that is part of a
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Science at MBZUAI focuses on the rigorous statistical and probabilistic foundations of machine learning and data science. We emphasize computational methods for large-scale data and scalable inference