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plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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Max Planck Institute for Physics, Garching | Garching an der Alz, Bayern | Germany | about 4 hours ago
and BAT.jl projects. The position also offers opportunities to contribute to research in Bayesian inference and its application to physics in general. The DEMOS project aims to develop state-of-the-art
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 3 hours ago
datasets to dissect cell states and communication networks in diseased and healthy tissues. Genetic and longitudinal modeling, integrating genomic variation with real-world longitudinal data—including
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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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the next. Your models will first be used to analyze completed experiments and identify trends, and later integrated into active learning and Bayesian optimization frameworks to suggest which experiments
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resonators) and quantum (NV diamond) sensor networks for thermodynamic metrology (temperature, pressure and humidity). key words Machine Learning; Bayesian optimization; Self-correcting; Quantum Sensors; NV
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The successful candidate will join a global network of Simons Postdoctoral Fellows in Strong Gravity and Black Holes that are part of the Simons-BHSG. This new, multidisciplinary and multinational collaboration