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position within a Research Infrastructure? No Offer Description Our theory group is a worldwide leader in studying the statistical physics of living systems, ranging from chromosomes to migrating cells and
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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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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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or Statistics or Business Intelligence, or Artificial Learning and Intelligence, or Signal Processing. o Skills in software development and databases. o Good general scientific background, particularly in
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Institut Supérieur de l'Aéronautique et de l'Espace | Toulouse, Midi Pyrenees | France | 19 days 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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. 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
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internationally in our research and study programs. In the newly established research group “Statistics & Data Science”, we develop and evaluate statistical models and analysis methods in psychology. Our research
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associated with diagnosing of Alzheimer’s disease? The Business Analytics Section at the Amsterdam Business School (University of Amsterdam ) invites applications for a PhD position in Statistics and Machine
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Your position You will become part of an international research group in an English-speaking environment. We pursue a range of topics in econometrics, statistics, data science, and stochastic models
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the data to statistically predict match outcome and league position. Initially, these models will be based on legacy data from our project partner, Scarlets Rugby. This dataset comprises individual athlete