Descripción
We are seeking a highly motivated predoctoral researcher to join the Digital Genomics Group within the Cancer Genomics Program at the CNIO. This is a unique opportunity to develop novel biomarkers using cancer genomics data, understand how diverse genetic and environmental factors shape tumor initiation and development, and 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 methodology across different cancer types, including colorectal cancer (Díaz-Gay, dos Santos, et al. 2025 Nature) and lung cancer in never smokers (Díaz-Gay, Zhang, et al. 2025 Nature).
The application should include:
• C.V.
• Motivation letter.
• 2-3 reference contacts Informal inquiries can be directed to Dr. Marcos Díaz-Gay (mdiazg@cnio.es), and more information is available at http://dg-lab.es/.
Criterios de evaluación
– Essential experience and skills:
• M.S. in computational biology, bioinformatics, biomedicine, machine learning, artificial intelligence, computer science, or related disciplines.
• Experience in genomics, epigenomics, transcriptomics, or human genetics.
• Proficiency in at least one programming language (preferably R and/or Python) and bash scripting.
• Solid level of spoken and written English (weekly meetings with English-speaking collaborators are expected).
– Desirable experience and skills:
• Experienced with high-performance computing (HPC) cluster systems and/or cloud computing.
• Experience in building well-documented and tested scientific software packages (GitHub contributions will be considered).
• Hands-on experience with bioinformatics tools for one of the following analyses: mutational signatures, variant calling or tumor evolution.
• Background knowledge in one of the following: colorectal or lung cancer biology, epidemiology, DNA repair, somatic mutagenesis, or machine learning methods.
Se ofrece
– Joining a research centre of international relevance.
– Competitive salary.
– Social benefits. Flexible compensation (Health insurance, meals, transportation, childcare).
– Estos contratos están vinculados a la acreditación del CNIO como Centro de Excelencia Severo Ochoa CEX2024-001442-S, financiado por el Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación (MICIU/AEI/10.13039/501100011033).