Principal Scientist, Research Analytics (Translational Informatics)
Other Locations:US- NJ- Summit West
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 lead work on the 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 rich patient data to empower data-driven decisions in collaboration with Celgene's Translational Development and Diagnostics organization.
Applications range from providing deep insight into therapeutic mechanisms of action for existing and novel therapies as they transition into clinic, identification and predictive leverage of patient phenotypes associated with therapeutic effect and outcome in key indications, and downstream development of molecular biomarker hypotheses into clinical diagnostics. Analysis scenarios will involve exploratory clinical data and output from transcriptomic, proteomic, genomic, and a wide range of innovative cell-molecular profiling platforms.
The position would suit an individual with strong scientific leadership potential and excellent communication and collaboration skills. Applications are encouraged from those involved in innovative translational biomarker research for complex oncology indications in clinical or industrial research environments. The role offers the opportunity to impact directly the delivery of truly transformational and life-changing therapies in key diseases of unmet medical need.
Strong interest in the inter-disciplinary application of computational analysis methods to life sciences data is imperative. Areas of particular focus include: elucidation of pleiotropic therapeutic actions via molecular profiling of complex cell culture models; methods to highlight clear mechanistic differentiation between compound mechanisms in key indications; and predictive patient stratification to identify biomarker-defined subgroups of unmet medical need and/or enriched therapeutic response via machine learning analysis of molecular profiling data.
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 line management of junior staff.
- Active participation as a core team member in the RIKU Research Analytics and Translational Development and Diagnostics groups.
- 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, influence decision making across the translational research and clinical development process, and feedback to inform early development of novel therapies.
- Data integration across assay platforms and knowledge transfer from pre-clinical experiments to clinical trials.
- Guide development of molecular patient selection and biomarker hypotheses towards clinical diagnostics.
- 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.
Background experience & complementary knowledge
- A Ph.D. in computational biology, bioinformatics, or related field from a recognized higher-education establishment.
- 7 years post-doctoral experience of inter-disciplinary computational and molecular biomarker research in university, hospital or biotechnology environments.
- 3 years experience in pharma/biotech research environment preferable.
- Strong knowledge required of predictive analytical practice and molecular diagnostic development. Working knowledge of clinical statistics desirable.
- 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 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.