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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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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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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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