Descripción

We are seeking a highly motivated Advanced Degree to join the Digital Genomics Group within the Cancer Genomics Program at the CNIO. This is a unique opportunity to deeply characterize different classes of somatic alterations using cancer genomics data, and to translate this knowledge into clinical settings.
In the recently established Digital Genomics Group (PI: Marcos Díaz-Gay), we aim to better understand the mechanisms behind the accumulation of genomic alterations in human tumors to benefit cancer diagnosis, prognosis, and treatment selection. By analyzing mutational patterns in tumors, we can identify the mutational processes active during tumorigenesis. These patterns, known as mutational signatures, are generated by different environmental, lifestyle and endogenous processes, and can be extracted from next-generation sequencing data using machine learning AI approaches. The group has recently demonstrated significant impact in applying this methodolog...