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to include more brilliant minds in our journey. See our publications and projects . DTU Compute DTU Compute – Department of Applied Mathematics and Computer Science – is an internationally unique academic
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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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calculus, linear algebra, probability and statistics, and possess strong proficiency in mathematical thinking and abstract reasoning. Cellular, biochemical, molecular experimental skills Experience working
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Ph.D. by the time of appointment in statistics, mathematics, computer science, engineering or a related discipline Required Other None Additional Preferred Experience working in one of the following
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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Computer Science, Applied Mathematics, Physics, Computational Biology, Neuroscience with Computational or Theoretical focus, or a closely related field. Preferred Qualifications: Familiar with Information Theory
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to disseminate research results QUALIFICATIONS Applicants must have (or be about to receive) a PhD in physics, biophysics, systems biology, applied mathematics, bioengineering, chemistry, chemical engineering, or
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Skip to main navigation Skip to content Skip to footer Skip to search Uni A-Z Contact Search Search (via Ecosia) Search Search Login Login Login Form Login Language Choose language German English Mainmenu Information for Prospective Students Current Students Staff Teaching...
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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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