Celgene is a global biopharmaceutical company leading the way in medical innovation to help patients live longer, better lives. Our purpose as a company is to discover and develop therapies that will change the course of human health. We value our passion for patients, quest for innovation, spirit of independence and love of challenge. With a presence in more than 70 countries - and growing we look for talented people to grow our business, advance our science and contribute to our unique culture.
We seek a talented, collaborative inter-disciplinary scientist to catalyze computational analysis of high-dimensional tissue, cell and molecular profiling data. This individual will play a key scientific role leveraging innovative computational analysis strategies and a wide range of data sources to empower data-driven decisions alongside colleagues in Celgene’s Research & Early Development organization. The role will align directly with the Celgene mission to improve therapeutic outcomes in complex diseases of unmet medical need.
Applications range from identification and investigation of novel therapeutic targets, elucidation of the therapeutic mechanisms of action for both existing and novel therapies, to generation of predictive molecular patient selection hypotheses early in the drug development cycle.
Analysis scenarios will involve data from a wide selection of cell-molecular profiling platforms, with particular focus on the identification of genetic biomarkers that relate to disease subgroups and therapeutic response. Other data sources will include genomic, transcriptomic, and proteomic assays applied to preclinical models and patient samples.
Data will arise from internal research efforts, partner organizations and public repositories. Expertise in genetic association studies and the analysis and interpretation of next-generation sequencing data are prerequisite.
The position would suit an individual with strong scientific leadership potential and excellent communication and collaboration skills. Applications are encouraged from those looking to bridge the gap between academic and industrial research environments to impact delivery of truly innovative and life-changing therapies.
Strong interest in the inter-disciplinary application of computational analysis methods to life sciences data is imperative, as is rich background and experience in bioinformatics and computational biology research. Areas of particular focus include systems-level analysis of genetic association studies to discover novel therapeutic targets, and use of phenotypic immune signatures to stratify large collections of patient molecular profiling data in key indications.
Working in collaboration with computational, biological and clinical scientists across the Celgene Research and Early Development organization, responsibilities include but are not limited to:
• Pursuit and supervision of leading computational biology research towards key Celgene scientific objectives, including potential line management of junior staff.
• Active participation as a core team member and subject matter expert in the Research Analytics group.
• Coordinated application of novel computational analysis and biological interpretation approaches to leverage internal, public and partner datasets and empower data-driven decisions across therapeutic programs.
• Multi-disciplinary collaboration to investigate compound and disease properties and influence decisions from target prioritization through to translational development.
• Data integration across assay platforms and knowledge transfer from pre-clinical experiments to clinical trials.
• Participation in and oversight of scientific report writing. Presentation of methods, results and conclusions to a publishable standard.
• Contribution to planning and execution of collaborative projects with leading academic and commercial research groups worldwide.
PhD and Post-doctoral experience in relevant discipline
Background experience & complementary knowledge
• A Ph.D. in genetics, computational biology, bioinformatics, or related field from a recognized higher-education establishment.
• 7+ years post-doctoral experience of inter-disciplinary computational and drug discovery research in university, hospital or biotechnology environments.
• 3+ years experience in pharma/biotech research environment preferable.
• Strong knowledge required of genetic association analysis and interpretation, and applied computational research on large multivariate datasets. Good working knowledge of predictive analytical practice is preferable.
• Previous experience of research supervision and track record of peer-reviewed publication in relevant scientific journals.
• Expertise in algorithmic implementation, statistical programming and data manipulation, using e.g. R/Bioconductor, Matlab, Python, and a wide range of contemporary, open-source bioinformatics tools and database structures.
• Proven problem-solving skills, collaborative nature and adaptability across disciplines.
• Excellent verbal and written communication skills. Fluent verbal and written English language skills prerequisite.
Celgene is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status.
Celgene complies with all applicable national, state and local laws governing nondiscrimination in employment as well as employment eligibility verification requirements of the Immigration and Nationality Act. All applicants must have authorization to work for Celgene in the U.S.
Req ID: 15002156
Primary Location: United States-California-San Diego
Job: Research and Development
Organization: Celgene Corporation
Employee Status: Individual Contributor
Job Type: Full-time
Job Level: Day Job
Job Posting: 2015-12-16 00:00:00.0
Biologist, Biology, Biotech, Data, Database, Engineering, Genetics, Healthcare, Medical, Molecular Biology, Open Source, R&D, Research, Research Scientist, Science, Scientific, Scientist, Statistics, Technology