DescripciónWe are looking for an enthusiastic and accomplished Research Scientist to join the Digital Genomics lab, focusing on cutting-edge cancer genomics research.
This is a unique opportunity to develop next-generation cancer biomarkers by leveraging mutational signatures, germline predisposition variants, and other cancer genomics features.
We aim to advance our understanding of how diverse genetic and environmental factors shape tumor development and how this knowledge can be translated into clinical settings to provide a better prognostic stratification and treatment selection for cancer patients.In the newly formed Digital Genomics lab (PI: Marcos Díaz-Gay), we are in 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.
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).We invite applications from senior postdoctoral researchers with a strong background in cancer genomics, epigenomics, transcriptomics, human genetics, or related fields, who are eager to shape the future of personalized cancer care.
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.Key Responsibilities: Develop next-generation AI-driven cancer biomarkers based on different genomics alterations and apply them to routine clinical sequencing data.Analyze diverse genomic data to assess population- and sex-specific differences in mutational processes, incorporating germline factors that influence cancer predisposition and progression.Collaborate closely with national and international partners to refine and validate biomarkers for clinical application.Essential Experience and Skills: PhD in biomedicine, computational biology, bioinformatics, machine learning, artificial intelligence, or related disciplines.At least 4 years of experience after PhD.Experience in cancer genomics, epigenomics, transcriptomics, or human genetics.Track record of publications and conference communications in the field.Proficiency in at least one programming language (preferably R and/or Python).Solid level of spoken and written English.#J-18808-Ljbffr