At Bristol Myers Squibb, we are inspired by a single vision - transforming patients' lives through science. In oncology, hematology, immunology, and cardiovascular disease - and one of the most diverse and promising pipelines in the industry - each of our passionate colleagues contributes to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference. CITRE, based in Seville, Spain, is Bristol Myers Squibb's research institute in Europe, and our link to the European research community.
Informatics & Predictive Sciences at CITRE performs innovative computational research to inform decisions across all stages of drug development. Areas of research include computational and network biology, machine/deep learning, cheminformatics, predictive modeling, patient stratification, and method development for analysis and interpretation of biological data. We seek an innovative Computational Scientist with experience in Systems Biology to join our team and contribute to the computational efforts at both early development and preclinical studies to guide translational research. This position offers the opportunity to directly impact the origination and development of novel therapies in oncology with unmet medical needs, as well as broad exposure to diverse clinical and analytical research challenges.
ResponsibilitiesCollaborate as a member of cross-functional teams to design, analyze, and interpret genomics, epigenetics, and proteomics experiments for elucidating mechanisms of drug sensitivity/resistance and prioritizing synergistic combinations.Perform analysis of clinical and preclinical genomic datasets using integrative and ensemble learning approaches.Participate in the scientific discussion of the results within a multidisciplinary team and translate the mechanistic findings from preclinical models to clinical settings.Author scientific reports to publishable standard.Contribute to planning and execution of collaborative projects with leading academic and commercial research groups worldwide. Background Experience & Complementary KnowledgePh.D. in computational biology, bioinformatics, biostatistics or related field from a recognized higher-education establishment.Statistical programming and data manipulation skills, using contemporary open-source bioinformatics tools (e.g., R/Bioconductor and Python) and databases using readable and reproducible code.Experience in computational cancer research applied to oncology, hematology, immunoinflammatory, and other therapeutic areas.Demonstrated ability to infer molecular mechanisms from NGS data generated by perturbation of in-vitro, in-vivo, and ex-vivo models using well-established bioinformatics tools and statistical methods.Familiarity with human interactome resources and databases (e.g., protein-protein interactions, regulatory and metabolic networks).Tracked record of peer-reviewed publications in top-tier scientific journals.
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