Bioinformatic Postdoc Position
The candidate will join a team coordinated by dr Luca Mazzarella and will operate at the interface between clinical and basic research to explore molecular mechanisms of cancer pathogenesis and therapeutic resistance, with a highly multidisciplinary approach
Specific interests in the lab are
-the interplay between chromatin and metabolism in cancer biology and immuno-therapy (Mazzarella et al Blood 2015 126:459, Rossi et al Science Adv 2016)
-the development of novel computational tools for the usage and interpretation of genomic data (see Melloni et al, Genome Med 2014, Breast Cancer Res Treat 2017, JCO Prec Oncol 2018)
-the exploration of resistance mechanisms to novel therapeutics in breast and ovarian cancers.
-the elucidation of molecular mechanisms underlying myeloproliferative neoplasms (MPN). On this topic, the lab was recently awarded a grant to elucidate genetic alterations associated with "triple-negative" and familial MPN, using novel long-read sequencing technologies (linked reads by 10x genomics, Nanopore sequencing), in collaboration with the University of Pavia, host to one of the largest existing collections of MPN samples.
The candidate shall operate within the IEO campus and in contact with the Clinical Genomics unit at IEO, within a large and expanding bioinformatics community. Available state-of-the-art facilities include Illumina Novaseq and HiSeq, ION Torrent S5, 10x Chromium, Oxford Nanopore sequencers.
The applicant must have excellent analytical skills, a strong statistical background, ability to work independently and as part of a team, very good oral/written communication and interpersonal skills to efficiently interact with the experimental collaborators and write and/or contribute to production of research reports and publications for peer reviewed journals.
Required skills are:
- A PhD-level background in a related discipline. Candidates with non-biological background, including Computer Science, Engineering, Mathematics, Statistics or Physics, are strongly encouraged to apply
- Experience in software and algorithm development
- Proficiency in the R environment
- Strong programming skills in at least one of the following languages: Python, Perl, Java, C++
- Proficiency in Unix/Linux operating systems
- Familiarity with High-Performance Computing
- Experience with analysis of large genomics datasets. Specific experience on Whole Exome/Genome Sequencing is desirable but by no means required
For further info or to arrange an informal interview, please write to