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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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spectrographs with various spectral resolutions, operating from 0.5 to 28 µm. Our group has developed the Bayesian modeling tool FORMOSA (Petrus et al. 2023). It allows the inference of low-resolution (R = λ/Δλ
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territories. The pedigrees reconstructed in each populations are sufficient to estimate some simple quantitative genetic parameters, but they are incomplete and contain errors, which greatly limits
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, so that it can be easily used in practice (fast optimization, embedded decision-making, online updating). 1. Design a lightweight statistical/probabilistic surrogate model, integrating: • an estimation
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, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates
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features to behavior using GLMMs/Bayesian models; conduct sensitivity and robustness checks. * Method validation: benchmark alternative pipelines (filters, burst detectors, forward/inverse models); perform