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Field
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computer science or statistics A solid background in mathematics, linear algebra and statistics. Documented experience with Bayesian spatiotemporal modelling, including experience with the INLA framework
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the following areas: applied mathematics, statistics, computational biology, biophysics, computer science, engineering, mathematical physics, or related disciplines. Reporting to Research Scientists
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Cryptography o Data Sciences, Complex Networks, Mathematical Biology o Quantum Computation & Information Science o Post-Quantum Cryptography, Homomorphic Encryption and Computing o Theoretical and Computational
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. Qualifications and personal qualities Applicants must hold a master's degree or equivalent education in Informatics, Physics or Mathematics, or must have submitted his/her master's thesis for assessment prior
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PhD Research Fellow in Experimental Fluid Mechanics: Tunable hairy surfaces for droplet flow control
of the fellowship is research training leading to the successful completion of a PhD degree. The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application
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, methods and applications. The areas represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and
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combining the mathematical and computational cultures, and the methodologies of statistics, logic and machine learning in unique ways, Integreat's machine learning will solve fundamental problems in science
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advanced degree (PhD) in physics, applied mathematics, chemistry or electrical engineering, and should have a background in experimental quantum systems. Experience with magnetic resonance, Hamiltonian
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of Mathematics and Natural Sciences. IFI is Norway’s largest university department for general education and research in Computer Science and related topics. The Department has more than 1800 students on bachelor
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program within a federal science agency. Mentor: The mentor for this opportunity is Mari-Vaughn Johnson (mvjohnson@usgs.gov ). If you have questions about the nature of the research please contact