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programming skills, in depth knowledge of MR theory, and experience with the acquisition and analysis of (preclinical) MRI data, as well as with mathematical modelling and image processing methods. Experience
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Postdoctoral Associate — Bioinformatics and Data Science - Stites Laboratory The Stites laboratory utilizes a variety of computational, mathematical, and experimental methods to study problems in
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mathematics skills, particularly in areas relevant to robotics and AI Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job
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of engineering, physical sciences, and mathematics. Pay and Benefits Pay Range: $61,008 - $65,000; depending on education/qualifications/experience Please visit the Benefits for Postdoctoral Candidates website
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for integration into diagnostic tools Preparing manuscripts for submission to both medical and machine learning journals Qualifications Candidate profile: Required: PhD in mathematics, statistics, data science
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: completed scientific higher education degree (PhD) in the field(s) of Earth system science, physics, climate physics, geosciences, mathematics, computer science or a comparable field demonstrated experience
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the Director of Center for Music in the Brain. Your competences You have academic qualifications at PhD level, for example within the following areas of neuroscience, engineering, mathematics, medicine
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A Research Associate post is available in the Global Coastal Wetlands Research Group directed by Thomas Worthington in the Department of Zoology at the University of Cambridge. The applicant will work on large-scale understanding of coastal wetlands - primarily mangrove forests and tidal...
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, mathematics, and innovation. Candidates must hold (or be close to completing) a Ph.D. in Applied Mathematics, Electrical or Mechanical Engineering, Physics and Applied Physics or a related field. Working in a
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advance the use of mathematical and statistical models of infectious disease transmission as tools for anticipating and addressing socioeconomic and geographic inequalities in infectious disease morbidity