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: Bayesian methodologies, temporal or geospatial prediction, network analysis, text analytics, statistical learning, or causal inference. Required Application Materials Electronic submission is
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the QISE department by carrying out both quantum information and computation projects ranging from quantum device characterization, error mitigation/suppression/correction, Bayesian-inference-based
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interests include Bayesian modeling and inference, causal inference, clinical trials, clustering, computational statistics, epidemic modeling, high-dimensional data analysis, longitudinal data analysis
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help develop personalised models. The practical element of your project will be based on, but not limited to, time series analysis, network analysis, Bayesian inference, Machine Learning, as well as
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Delft University of Technology (TU Delft) | Delft, Provincie Zuid-Holland | Netherlands | 5 days ago
or clinical research questions or to tackle methodological problems in medical applications. Specific requirements: Demonstrated experience in Bayesian inference / networks; Familiarity with
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are not limited to, statistical learning and machine learning, Bayesian methods, causal inference, functional data analysis, longitudinal and spatiotemporal data analysis, high-dimensional data
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. Expertise in Bayesian methods, generative models, multimodal models, world models or simulation-based inference is meriting, as is experience with large-scale training on GPU clusters, open-source
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modern computational statistics, statistical genetics, spatial statistics, Bayesian inference, time series, categorical data analysis, bioinformatics, analysis of medical images, data visualization
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limited to, statistical learning and machine learning, Bayesian methods, causal inference, functional data analysis, longitudinal and spatiotemporal data analysis, high-dimensional data, statistical
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Wageningen University & Research | Wageningen, Provincie Gelderland | Netherlands | about 2 months ago
approaches for uncertainty quantification, large-scale prediction, model-based learning, causal inference, network learning, or related areas. Experience with Bayesian methods, whether theoretical