318 computer-science-quantum-"https:"-"https:"-"https:"-"https:" research jobs at Nature Careers
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, the Division of Signaling and Functional Genomics at the German Cancer Research Center is seeking as soon as possible a Postdoc – Bioinformatics / Computational Biology Reference number: 2026-0007 The Division
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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intelligence, quantum chemistry, and quantum computing. Individuals with bold vision and who demonstrate excellence in research at the interface of chemistry, biology, and medicine are encouraged to join our
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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in
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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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, the Division of Signaling and Functional Genomics at the German Cancer Research Center is seeking as soon as possible a Postdoc – Bioinformatics / Computational Biology Reference number: 2026-0007 The Division
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We are seeking applicants for a 2-year postdoc in Ultrafast X-ray probes of Quantum Materials to join us at the Department of Physics and Astronomy. Starting Date and Period The position is for 2
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interdisciplinary, and together we contribute to science and society. Successful candidates will join the Computational Biology group, led by Prof. Antonio del Sol, which develops computational models to address
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interdisciplinary, and together we contribute to science and society. Successful candidates will join the Computational Biology group, led by Prof. Antonio del Sol, which develops computational models to address
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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