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Field
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research projects at the intersection of infectious disease modelling, Bayesian inference, AI, and public health. Projects span AI-driven epidemic forecasting, transmission modelling in the ASEAN region
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, internationally connected research programme spanning Bayesian infectious disease modelling, AI-driven epidemic forecasting, genomic epidemiology, and pandemic preparedness. The postholder will work with Asst. Prof
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conducting synthesis research on crop diversification across a range of environmental conditions. The DRIVES database is a network of data from long-term cropping systems experiments. The Associate will be
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considered. Technical expertise and deep knowledge of one or more of the following areas: Physics-informed neural networks (PINNs) & surrogate modelling Time-series modelling & anomaly detection Bayesian
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
modeled using an evolution of this algorithm, which replaces the SVRs with a multilayer neural network [Ribes et al., 2024]. In 2025, it was used in an inverse-computation context using Bayesian inversion
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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific
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statistical analysis including multivariate methods, data reduction techniques, structural equation modeling, survival analysis and Bayesian hierarchical imaging models, graph neural networks. The specialist
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international projects such that the successful candidate will have excellent opportunities to participate in international research networks. We also run an advanced drone lab on behalf of the entire faculty
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
. 5. Y. Ban, X. Alameda-Pineda, L. Girin, and R. Horaud, "Variational Bayesian inference for audio-visual tracking of multiple speakers," IEEE TPAMI, 2019. 6. X. Alameda-Pineda et al., "Socially
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: Physics-informed neural networks (PINNs) & surrogate modelling Time-series modelling & anomaly detection Bayesian methods & uncertainty quantification LLMs & multi-modal models Graph neural networks (GNNs