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cell tracking to identify the progenitors of these cells during regeneration. • Develop and apply a recombinase-based cell barcoding strategy to trace cell lineages during leg growth and regeneration
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, optimization, dynamic systems, decision theory, Bayesian inference) ● Is motivated to apply these methods to ecological, evolutionary, and conservation systems; ● Is comfortable with uncertainty, modeling
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, hydro-acoustics, data science, geodynamics, geophysics, statistics, Bayesian inference ⁃ Experience with statistical analyses and machine learning techniques ⁃ Programming in C / python / Julia
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maximum likelihood and Bayesian inference frameworks. - Data mining in genome databases. - Large-scale phylogeny reconstruction (archaea, bacteria, and eukaryotes). - Implementation of complex sequence
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canopy height inference methods accurately represent the variability observed in Central African forests. The research associate will work at the CNRS in Toulouse and will be involved in the activities
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parameter estimation using Bayesian inference, and/or the exploitation of Machine Learning (ML) based algorithms to reduce false positives caused by human generated interference signals in the observational
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Description You will: * Lead MEG head-cast data collection for a visuomotor reaching/interception study, ensuring robust synchronization with video-based kinematics and eye-tracking, and enforce rigorous
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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uncertainties (delays, resources, failures) using various methods, including Bayesian approaches. 3. Optimize the workshop configuration, taking into account scenario variability, by relying on the surrogate
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-junction components; integration with immune signatures to infer causal relationships. 5. Data management & integration: produce clear datasets with documented data; contribute to interim and final reports