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Specific Requirements You hold an MSc in Statistics, Mathematics, Artificial Intelligence, or a closely related discipline; You have a strong background in quantitative modeling enabling the development
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://www.tudelft.nl/ewi/over-de-faculteit/afdelingen/applied-mathema… ) is offering a full-time PhD position in the area of Multivariate dependence modelling and statistical machine learning algorithms for patient
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3 Apr 2024 Job Information Organisation/Company University of Gothenburg Research Field Physics » Statistical physics Researcher Profile First Stage Researcher (R1) Country Sweden Application
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PhD position in the area of Multivariate dependence modelling and statistical machine learning algorithms for patient risk profiling. In partnership with RECENTRE (see https://www.4tu.nl/recentre/), a
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prominent place in Scandinavian mathematics. The department consists of three divisions: mathematics, computational mathematics and mathematical statistics. Researchers at the division of mathematical
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educational technology. You will become part of the Department of Methodology and Statistics and will join an active research group in psychometrics. This project is supervised by dr. Maria Bolsinova, dr
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Institut Supérieur de l'Aéronautique et de l'Espace | Toulouse, Midi Pyrenees | France | 3 months ago
mathematical and signal processing background, with strong skills in Matlab/Python. Knowledge on: GNSS; estimation theory; statistical analysis; are a plus. Demonstrated interest in remote sensing, GNSS, signal
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. Analyses will include information from population-based cohorts (e.g. the EAGLE consortium ) and clinical collections (e.g. samples from the Simons Foundation ). Statistical analyses will include
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algorithms. Requirements Research FieldMathematicsEducation LevelBachelor Degree or equivalent Skills/Qualifications Required skills: · Degree in statistics, data sciences, mathematics, or related disciplines
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. The theory will build upon ideas from information topology, information geometry, and statistical modeling. We will aim to address the question: “How can one detect and characterize emergent properties of real