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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Unleashing the potential of Bayesian statistics to predict the performance of new
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(NSSD). In this role, you will conduct fundamental research into the integration of Bayesian methodologies with system dynamics modeling, advancing statistical methods and the open-source scientific
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modelling, Bayesian inference or gradient-based inference methods. Experience with automatic differentiation frameworks such as JAX or PyTorch would be an advantage, as would experience with tools
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constitutive parameters from a single informative test through Bayesian optimization, together with quantification of measurement and model-form uncertainty. Approximately half of the effort will extend
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for scientific applications. Robotics, active learning, Bayesian optimization, molecular representations, or scientific data infrastructure. Polymers, membranes, or electrochemical characterization and analysis
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Qualifications: Experience using the MOOSE simulation framework is highly desired. Experience fitting complicated physics-based models against test data, including machine learning and Bayesian optimization
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Bayesian meta-analyses. This position also provides opportunities to develop innovative statistical methods related to clinical trial design, variable selection in high-dimensional data, prediction
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mammal bioacoustics; machine learning; Bayesian statistics; statistical simulations of individual/group behavior; spatially explicit capture-recapture modeling; and/or habitat modeling are preferred
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dinosaurs, squamates, and amphibians). They will use Bayesian statistics to test for trends in brain size change over time and phylogeny, test for correlations between brain size and neuron counts in extant
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. Physics, Engineering, Computer Sciences, Neurosciences), and a PhD in a relevant computational domain. Also deep knowledge of statistics and Bayesian learning, and necessary mathematical and computational