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Systems and Software Program (WASP ). You can find more information about us on the Department of Information Technology website. The position is hosted by the Division of Scientific Computing (TDB), one
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department each year. You can find more information about us on the Department of Information Technology website . At the Division of Systems and Control , we develop both theory and concrete tools to design
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, doctoral students and administrative staff, together with around ten teaching assistants. Our research spans a range of statistical fields, including high-dimensional data analysis, Bayesian methods, spatio
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. Application of Bayesian mixing models to investigate consumer diets and food web pathways Requirements To meet the general entry requirements you must have been awarded a second-cycle (Master’s) qualification
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, Bayesian inference, model calibration, and Markov Chain Monte Carlo methods, uncertainty quantification, statistical modelling, and Gaussian processes, machine learning for time series, sequence-to-sequence
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chromatographic techniques. Integration and synthesis of previous data with newly collected data on fatty acids, cyanotoxins, and stable isotopes. Application of Bayesian mixing models to investigate consumer diets
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students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the Department of Information Technology website
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) signalling, adjusting the wall's properties when they are threatened. A central question remains unresolved in both plants and algae: what does a CWI sensor actually detect? The difficulty is that the stresses
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their susceptibility to side effects. Laboratory methods are therefore needed to better predict individual treatment toxicity. Aim/objectives To develop and validate blood-based functional assays for predicting bone
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, mixed-effects modeling, Bayesian methods, deep learning, variational autoencoders, generative AI). Is an experienced programmer in R and/or Python, and used to working with large datasets and reproducible