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. et al. (2024). Design of high-performance entangling logic in silicon quantum dot systems with Bayesian optimization. Scientific Reports 14, 10080. https://doi.org/10.1038/s41598-024-60478-9
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Design, Modelling and Simulations (MATHDES) group, and work under the supervision of: Matteo Croci. Google Scholar: https://scholar.google.com/citations?user=AmQKnwcAAAAJ&hl=en CV: https://croci.github.io
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, United States of America [map ] Subject Areas: Bayesian inference; inverse problems Appl Deadline: 2025/12/31 11:59PM (posted 2025/10/09, listed until 2026/04/09) Position Description: Apply Position Description
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, particularly radionuclides, on a continental scale. The aim is to develop a new class of inverse Bayesian models, STE-EU-SCALE, combining innovative forward dispersion models, machine learning techniques, and
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understanding of statistics (e.g., hypothesis testing, Bayesian statistics) Good collaborative abilities, independence, and critical thinking. Preferred qualifications In-depth experience with LLM agents
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of Biostatistics and Population Health (BPH, https://medicine.osu.edu/departments/biomedical-informatics/divisions/division-of-biostatistics-and-population-health ) in the Department of Biomedical Informatics (BMI
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, implementation science, geospatial analysis, biostatistics and research design, AI analytics, agent-based modeling, Bayesian modeling, causal inference, and measure development. We are seeking exceptional mid
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Investigate the use of causal discovery methods in "concept drift" situations in structural causal models. In semiparametric Bayesian networks, investigate the selection of covariance matrices and the
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Description Distribution estimation algorithms for abductive inference (total or partial) in dynamic domains. Structural learning of dynamic Bayesian networks with discrete and continuous variables (parametric
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University of California, San Francisco | San Francisco, California | United States | about 16 hours ago
– a public-private partnership conducting phase II trials of new regimens for the treatment of tuberculosis (https://www.unite4tb.org/). Application of Bayesian methods for evidence synthesis