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leading aerospace organizations. It is a subproject of a NATO-wide initiative where participating organizations can test new control algorithms on sub-scale 3D-printed aircraft, developed and provided by
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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is characterized by a modern view of the statistical subject, where probabilistic models are combined with computational algorithms to solve challenging complex problems, as well as a statistical view
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uncertainties. Determining how to account for these uncertainties leads to research questions spanning from data collection and estimation to model representations and optimization algorithms. In the field
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research on the development of new inference methods and algorithms for wide classes of stochastic models. However, research will be conducted in collaboration with biologically oriented researches allowing
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strong background in mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. The applicant should furthermore
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successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment