Bayesian statistics in RNA sequencing and epidemiology

Bayesian statistics is playing an increasing role in the life sciences and it recognized as one of the fundamental tools for the analysis of experimental data. In fields like systems biology, genetics and
even epidemiology, new data become available every day with the increase capacity of the technologies, and statistical methodologies need to keep up with these developments.

The research activity fits in the SmartData@PoliTo interdepartmental centre, that brings together competences from different fields, ranging from modelling to computer programming, from communications to statistics. The candidate will join this interdisciplinary team of experts and collaborate with them.

The aim of the project is to develop better statistical methodologies that can improve the analysis of data that the technological development (and the need to fight the pandemic) has made available in recent years. A first line of research will be to extract more information from single cell RNA  equencing data (scRNAseq). Some statistical tool for the analysis of this data is already available, but both the technology and our capacity of interpreting the underpinning phenomena is increasing fast. We believe that better methodologies are feasible, and that Bayesian statistic can play an important role.
A possible second line of research is to use a similar Bayesian framework for the surveillance of the spreading of the infection of the Sars Cov 2 virus (expecially the new variants), when (and if) more sequencing data will become available.

• MSc, Laurea or equivalent degree in applied mathematics, statistics, physics, computer engineering, data science or related fields;
• at least 15 credits in Probability and Statistics;
• Good programing skills in R, Python, Matlab, or other languages;
• Some basic Bioinformatics is welcome but notstrictly necessary.