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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 1 day ago
also opens perspectives for applying and extending continuous Bayesian networks and bandit-based experimental design approaches to agricultural systems. Because of the computational demands of crop
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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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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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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | about 1 month 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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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization
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, 2022) and extended this to the triple equivalence between neural dynamics, Bayesian inference, and algorithmic computation (Commun Phys, 2025). -We validated it within in vitro neural networks (Nature
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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