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Field
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modern clinical trial design, such as Bayesian Adaptive Clinical trial design or established expertise in statistical methods such as structural equation modeling, causal data analysis. Experience in
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personalizable computer replica of the immune system – to enable everyone and anyone to assess and optimize the health of their immune system and simulate and predict its future ability to respond to diseases. Why
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benefiting greatly from overlap with strengths in spatial and quantitative ecology. Our modelling is developed in close proximity to data, and focused on estimation of parameters relevant to dynamics and
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project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision or physics-informed machine learning, develop robust surrogate forward models to predict
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Virol 69, 96-100 (2015). C. Mair et al., Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models. PLoS Comput Biol 15, e1007492 (2019). Option B: Create
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the Faculty of Science. We will apply Bayesian approaches such as the information-theoretic minimum message length (MML) principle and other approaches to develop a path towards statistically-optimal algorithms
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-portals and visualizations for complex data Building models and sensors for the estimation of ecosystem carbon exchange in urban and forested environments. Candidates will be expected to contribute
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back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum message length (MML) approach (Wallace and Boulton, 1968
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Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum
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for the prediction task, such as predicting the bioassay of a given chemical network. One of the approaches that will be considered will be the Bayesian information-theoretic Minimum Message Length (MML) principle