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Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of dynamic sequential inference
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lattice orientation by EBSD or local chemical composition by EDX [1]. For instance, an original protocol based on Bayesian inference was recently co-developed by LEM3 and ICA to determine the single-crystal
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
Bayesian statistics, AI-assisted inverse problems, planetary remote sensing, and environmental monitoring. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-09787 Requirements Skills
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be inferred from models that are incomplete and data that involve errors. For such challenges, Bayesian analysis using Markov Chain Monte Carlo (MCMC) has become the gold standard. For addressing high
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biostatistical training and skills, including longitudinal and correlated data; familiarity with advanced analytics including machine learning, Bayesian methods, and causal inference also desired. Strong written
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relevant to modern data science (e.g., Bayesian or frequentist inference, information theory, uncertainty quantification, high-dimensional methods). Programming skills in Python and/or R, with evidence of
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Bayesian Index Tracking: optimisation by sampling School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Kostas Triantafyllopoulos, Dr Dimitrios Roxanas Application
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conduct research in several areas: analysis of high-dimensional data, Bayesian methods, spatial-temporal models, non-Gaussian modeling, applied research in social science, as well as stochastic models and
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expertise in areas such as approximate inference, Bayesian statistics, continuous optimization, information geometry, etc. We work on a variety of learning problems, especially those involving supervised