The Cortes-Ciriano group studies the mutational processes and mechanisms of genome instability underpinning tumorigenesis, immune escape, and drug response through the analysis of multi-omic, high-throughput data of tumors and pre-clinical models.
Ultimately, we aim to uncover novel pharmacological targets for cancer therapy and biomarkers of drug response. More information about the group can be found here.Your roleWe invite applications for a Postdoctoral Fellow position in the field of cancer genomics. We are looking for an intrinsically motivated, talented, and hypothesis-driven individual with experience in analyzing high-throughput sequencing data sets to join a set of sequencing projects involving samples spanning multiple cancer types. This position is an excellent opportunity for individuals looking to gain in-depth knowledge and expertise in cancer genomics and to develop bioinformatic skills for analyzing and interpreting large genomic data sets.
You will be expected to lead the development of scalable and creative computational solutions for cancer multi-omic data integration. Specifically, your project will involve developing computational pipelines for analyzing and interpreting data from bulk sequencing (RNAseq, whole-genome, and whole-exome) and single-cell sequencing (scRNAseq) of human tumor samples that our clinical collaborators have collected. The results of these analyses will be combined with those obtained by major pan-cancer genome analysis efforts (e.g. TCGA) in order to inform the design of additional sequencing experiments. It is essential that you are dedicated to lead your own project while also being a team player and willing to engage with our international collaborators. You will enjoy substantial freedom to design novel algorithms for sequencing data analysis and to explore your own hypotheses developed within the scope of these projects.
Your project will benefit from close interaction with the clinical oncology laboratories generating the sequencing data, local and international collaborations in cancer biology, genomics and bioinformatics.