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Field
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theory, stochastic dynamical systems, hierarchical Bayesian models, optimization, mean field games, and applications of these methods to renewable energy related topics such as atmospheric modeling, wind
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the analysis of massive datasets. Extensive experience in signal processing and advanced statistical inference (e.g., Bayesian statistics, Fourier analysis) for extracting robust patterns from noisy, high
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part of a team Understanding of dynamical systems, time series models, machine learning, Bayesian statistics, experience in handling environmental and climate data is a merit We offer: This position is
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to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field
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intelligence, machine learning, big data and network analysis, computational and Bayesian methods, are encouraged to apply. Minimum Qualifications PhD in Statistics or closely related fields with documented
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close to the nest [1 ] but to better understand foraging, we need landscape level detail. The direction of the project can be tailored, but could include developing and applying Bayesian ML approaches
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applications. The project aims to address fundamental theoretical questions related to the representation and measurement of the polarization state, as well as the use of Bayesian and/or statistical learning
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. Candidates with either Bayesian or traditional statistical backgrounds are encouraged to apply. Candidates should be able to programme in a high-level language for data analysis such as R, STAN or MatLab
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application of conditional diffusion models, flow matching techniques, or related generative approaches, as well as experience working with probabilistic (Bayesian) methods and statistical modelling. Strong
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evidence synthesis, including Bayesian inference as well as effective interpersonal skills. You will work alongside an interdisciplinary team to deliver the research aims. In addition, the postholder will be