-
, supervised and unsupervised machine learning, and complex data fusion; proficiency in parametric and non-parametric statistical methods, bootstrapping simulation techniques, and experimental design; advanced
-
-mantle NCMASF3 system; ii) Training a Mixture Density Network emulator on 106 thermodynamic evaluations; iii) Implementing a global MCMC Bayesian inversion of the SPARTANS tomographic model; and iv
-
in molecular biology, with emphasis on primer design and validation and gene expression analyses. Proficiency in statistical analyses, including multivariate approaches and mixed models. Established
-
genome evolution. How to apply Email subject: “PD-CitrusGenomics”. Include: Lattes CV & Curricular Summary (FAPESP Model ) or CV for international candidates; copy of Ph.D. certificate/diploma; cover