Descripción We are looking for a highly motivated postdoc to develop innovative computational methods to analyze mutational signatures and tumor evolution using human cancer sequencing data.
In the newly formed Digital Genomics lab (PI: Marcos Díaz-Gay), we are in the pursuit of understanding better 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 the tumorigenesis process.
Thus, specific patterns of mutations, known as mutational signatures, are generated by different environmental (e.g., ultraviolet light exposure), lifestyle (e.g., tobacco smoking), and endogenous processes (e.g., defective DNA repair mechanisms).
Mutational signatures can be extracted from next-generation sequencing (NGS) data using machine learning artificial intelligence (AI) approaches and assigned to individual tumors for patient-level analyses, as previously shown (Islam & Díaz-Gay et al.
2022 Cell Genomics, Senkin et al.
2024 Nature).
Using publicly available NGS data, as well as leveraging our national and international collaborations, we have the opportunity to apply these AI approaches in a cohort of >20,000 whole-genome sequenced tumors, with patients collected across >30 countries, four continents, and multiple tumor types.
We are seeking an enthusiastic postdoctoral researcher to develop innovative computational methods to further characterize mutational signatures in human cancer, with the goal of precisely mapping the genomic fingerprint of epidemiological factors and molecular alterations contributing to the risk of developing cancer.
The diverse cohort collected will also allow the elucidation of population and sex-specific differences across cancers originating from geographical regions with distinct incidence and mortality rates.
As the lab is in its founding stage, this position offers the chance to make a foundational impact and help shape a collaborative and dynamic team, fostering a supportive and inclusive work environment.
"La financiación de estos contratos, procede del Mecanismo de Recuperación y Resiliencia de la Unión Europea-Next Generation, en el marco de la Invitación General de la entidad pública empresarial Red.es para participar en los programas de atracción y retención del talento dentro de la Inversión 4 del Componente 19 del Plan de Recuperación, Transformación y Resiliencia."Criterios de evaluaciónWe are seeking an enthusiastic and driven scientist with the following competencies and experience.
Essential experience and skills: • PhD in computational biology, bioinformatics, statistics, computer science, machine learning, artificial intelligence, or related disciplines.
• Experience in at least one of the following: cancer genomics/transcriptomics, evolutionary biology, human genetics, germline predisposition, biostatistics, or machine learning.
• Proficiency in at least one programming language (preferably R and/or Python).
• Solid level of spoken and written English.
Desirable experience and skills: • Experience with high-performance computing (HPC) cluster systems and/or cloud computing systems.
• Experience in building well-documented and tested scientific software packages.
• Hands-on experience with bioinformatics tools for one of the following analyses: mutational signatures, mutation calling, or tumor evolution.
• Additional experience with molecular biology techniques (wet lab) and background knowledge in colorectal or lung cancer biology will be considered.Se ofrece• The opportunity to be part of an internationally renowned cancer research center of excellence.
• Collaborative, supportive, and inclusive work environment.
• Competitive salary.
• Contract linked to a project.