- 2020-ongoing, Tenure track researcher. Department of Mathematics and Geosciences, University of Trieste.- 2020-ongoing, Core Faculty, PhD program in Applied Data Science & Artificial Intelligence, University of Trieste.- 2020-ongoing, Adjoint Faculty, PhD program in Theoretical and Scientific Data Science, SISSA.- 2020-ongoing, Honorary fellow, The Institute of Cancer Research, UK.- 2017-20, The Institute of Cancer Research, UK. Laboratory of Cancer Evolutionary Genomics and Modelling (PI Andrea Sottoriva).- 2015-17, University of Edinburgh, UK. Laboratory. of Machine Learning for Computational Biology and Bioinformatics (PI Guido Sanguinetti).- 2011-15, University of Milan-Bicocca, Italy. Laboratory of Bioinformatics and Systems Biology (PI Giancarlo Mauri, Marco Antoniotti). - 2011, PhD in Computer Science (University of Pisa).- 2008, BSc, MSc in Computer Science (University of Pisa).
- BSc, MSc in Physics (University of Pisa);- PhD in Physics and Chemistry of Biological Systems (SISSA).
Topic: Artificial Intelligence for clonal evolution under therapy.
- BSc in Biotechnology (University of Turin);- MSc in Quantitative and Computational Biology (University of Trento)- PhD Student in Applied Data Science & Artificial Intelligence, University of Trieste.
Topic: computational modelling of biological processes.
email@example.com Co-mentored with Andrea Sottoriva (Human Technopole).
- BSc in Genetics (University of Padova);- MSc in Data Science and Scientific Computing (University of Trieste)- PhD Student in Computational Biology, European School of Molecular Medicine, Milan.
Topic: statistical methods for longitudinal single cell sequencing.
firstname.lastname@example.org Co-mentored with Marco Antoniotti and Alex Graudenzi (Milan-Bicocca)
- BSc in Computer Science (University of Milan-Bicocca);- MSc in Computer Science (University of Milan-Bicocca);- PhD student in Informatics, Milan-Bicocca.
Topic: multi-omics single-cell data integration.
Master and Bachelor students
Program: MSc Data Science and Scientific Computing.Topic (MSc thesis): Statistical models for spatial transcriptomics
Program: MSc Data Science and Scientific Computing.Topic (MSc thesis): mutational signatures deconvolution.