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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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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | 11 days ago
Job Code: 07/2025 Job Offer from November 21, 2025 We are seeking to fill one postdoctoral position as part of the Simons Collaboration on Learning the Universe . In this international network
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: Cuantificación de Incertidumbre Bayesiana (Bayesian Uncertainty Quantification, BUQ) Appl Deadline: 2025/10/30 11:59PM * (posted 2025/09/08, listed until 2025/10/30) Position Description: Apply Position
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uncertainty from climate projections into land-use forecasts. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models
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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | 18 days ago
dynamics in health and pathology; (2) in silico models, including Bayesian models, neural mass models and spiking neural networks; (3) in vitro neuronal network measurements. Our aim is to innovate in
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Observatory Network to model individual size distributions of macroinvertebrates and fish. This will include extensive travel to field sites throughout the US to conduct in situ metabolic scaling experiments
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Observatory Network to model individual size distributions of macroinvertebrates and fish. This will include extensive travel to field sites throughout the US to conduct in situ metabolic scaling experiments
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Observatory Network to model individual size distributions of macroinvertebrates and fish. This will include extensive travel to field sites throughout the US to conduct in situ metabolic scaling experiments
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) physics. Desirable Expertise in computational fluid mechanics, broadly construed. Expertise in Bayesian methodology for optimization and experiment design. Experience with equivariant neural networks. Track
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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization