295 computational-physics "https:" "https:" "https:" "https:" "The University of Manchester" Postdoctoral research jobs at Nature Careers
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part of an interdisciplinary team working across physical and computer science to develop new pathways to the design and discovery of inorganic materials as part of the Leverhulme Centre for Functional
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opportunity to learn the process and challenges of drug discovery from the inside, including additional training and mentoring program. In addition, benefit from the rich packages for employee benefit. Our most
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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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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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systems and a vibrant interdisciplinary community at Aarhus University, including collaborators in biophysics, neurodegeneration, spectroscopy, and computational modeling. You would join a dynamic research
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Experience in planning and conducting field-work Experience in planning and conducting laboratory work within nitrous oxide field measurements, soil sampling and the quantification of soil physical, biological
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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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Sustainable travel to work: subsidized Germany job ticket Our Corporate Health Management Program offers a holistic approach to your well-being Develop your full potential: access to the DKFZ International
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, who go on to pursue our mission at MSK and around the globe. The Norman Lab is seeking a postdoctoral researcher to join our team. We're a hybrid experimental-computational group in the Computational
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immunogenicity. Over the past decade, this process has been well characterized, and robust methods have been developed to predict it with high confidence. In contrast, our understanding of the principles governing