General Description
Place: San Raffaele Telethon Institute for Gene Therapy (hSR-TIGET), Via Olgettina, 58, 20132 Milano, Italy
Contract: Co.Co.Pro
Career Level: Livello iniziale
Education: Laurea Spec./Vecchio Ord. in Statistica, Matematica, Bioinformatica
Area: R&D
Starting date: From January 2013 on.
Job description
Our group is in charge of handling data from viral integration studies [1, 2, 3] at TIGET for both clinical and preclinical studies. Vector integration sites (VIS) are genomic positions annotated with respect to reference genome (human or mouse): we built a bioinformatics pipeline to identify VIS from sequencing reads (454 and Illumina) and we collected data (BED-like file format) in a database storing metadata such as cell type, harvest time point and tissue.
We are studying VIS within systems biology perspectives, trying to understand cell dynamics during time and modeling stem cells growth and differentiation to analyze safety of gene therapy and biological data mining. Our candidate will be involved in statistical methods for VIS data analysis and systems modeling and simulation.
Candidates could apply to PhD programs in Statistics, Bioinformatics or Computer Science working on our project.
[1] Naldini, L. (2011). Ex vivo gene transfer and correction for cell-based therapies. Nature reviews. Genetics, 12(5), 301–15. doi:10.1038/nrg2985
[2] Biffi, A., Bartolomae, C. C., Cesana, D., Cartier, N., Aubourg, P., Ranzani, M., Cesani, M., et al. (2011). Lentiviral vector common integration sites in preclinical models and a clinical trial reflect a benign integration bias and not oncogenic selection. Blood, 117(20), 5332–9. doi:10.1182/blood-2010-09-306761
[3] Biasco, L., Baricordi, C., & Aiuti, A. (2012). Retroviral Integrations in Gene Therapy Trials. Molecular therapy : the journal of the American Society of Gene Therapy, 1–8. doi:10.1038/mt.2011.289
Requirements
The ideal candidate is seeking a long-term commitment. He/she is a young motivated and enthusiastic researcher, possibly committed to undertake a PhD program in Statistics, Bioinformatics or Computer Science/Engineering.
Preferred experiences/skills: theoretical and practical statistical approaches (FDR analysis, parametric and non-parametric tests, multivariate analysis, etc), algorithm development; basic programming languages and statistical frameworks (i.e. Python/Perl, R/Matlab).
Contact
Please send your application including a synopsis of research interest and Curriculum vitae by email to: Andrea Calabria (calabria.andrea@hsr.it)
