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 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. Specific patterns of mutations, known as mutational signatures, are generated by various 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 and 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, along with our national and international collaborations, we have the opportunity to apply these AI approaches in a cohort of over 20,000 whole-genome sequenced tumors, with patients collected across more than 30 countries, four continents, and multiple tumor types. We seek an enthusiastic postdoctoral researcher to develop innovative computational methods to further characterize mutational signatures in human cancer, aiming to precisely map the genomic fingerprint of epidemiological factors and molecular alterations contributing to cancer risk.
The diverse cohort collected will also allow for 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.
Criterios de evaluación We 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.
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