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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. Automated data-driven selection procedures will enable to gain objectivity and capacity to handle large amount of data from a wide range of epidemics. The first challenge consist in refining previous models
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. The inventory is still ongoing, but our field is now heavily investing in the characterization of the physical and chemical properties of these objects through the use of sensitive imaging cameras and
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Division, which also includes the DELPH (Detection and Lasers for Physics) and GTA (Acquisition Techniques Group) groups. The division's staff are responsible for hosting experiments at GANIL by
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, such as Bayesian approaches and fossilized birth–death models, to reconstruct robust phylogenies and estimate divergence times. It also investigates macroevolutionary dynamics, including variation in
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The main objective of the postdoctoral fellow's work is to develop an imaging Mueller polarimetric system for improving the detection and quantification of abiotic stress in plants. The post-doctoral fellow
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project focuses on estimating dead fuel produced by forest dieback. In previous projects, a processing chain using Sentinel-2 data has already been developed (Mouret et al., 2024). The objective here is to
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, seismology, geophysics or a relevant scientific field Have extensive experience in Bayesian statistics, mathematical optimisation and parallelisation of calculations Be familiar with ground motion analysis
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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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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 14 days ago
objective of this position. The initial research direction in this post-doctoral position is to study variants of modern random access, incorporating realistic physical-layer features and methods (e.g., [5,6
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applications. The project aims to address fundamental theoretical questions related to the representation and measurement of the polarization state, as well as the use of Bayesian and/or statistical learning