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methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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and Preservation Apply by Sep 30, 2025 · College of Dental Medicine Open until filled · Zuckerman Institute No results found matching that criteria. Please update the keywords and filters.
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to offer. Qualifications: Required: PhD in ecology by start date Experience in plant phenology, biogeography, and spatial and temporal modeling (Bayesian and frequentist) Expertise in R or Python, GIS, big
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mathematical background, including expertise in stochastic optimization (e.g. Markov decision theory and dynamic programming) and applied probability (Bayesian statistics). Excellent coding skills (e.g., in Java
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: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and
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to implement advanced computational pipelines, including machine learning, deep learning, Bayesian inference, and probabilistic mixed membership modeling for innovative research. · Contribute
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experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will
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(2024). 2. Multiresonant Grating to replace Transparent Conductive Oxide Electrode for bias selected filtering of infrared photoresponse, Tung H. Dang, M. Cavallo, A. Khalili, C. Dabard, E. Bossavit, H