Pfizer Sr. Computational Biologist, Tumor Cell Biology in La Jolla, California
We are looking for a talented and highly motivated computational biologist to join a team supporting discovery and development of new therapies targeting tumor intrinsic mechanisms with a focus on Cell Cycle and Epigenetics. The scientist will work in an inter-disciplinary environment and have the opportunity to advance discovery and development of cutting-edge cancer therapeutics. The scientist will closely collaborate with bench biologists to elucidate molecular mechanisms of novel cancer therapies and identify patients most likely to benefit from new and existing therapies. In collaboration with translational oncology leads, the scientist will analyze and interpret data from early clinical development of cancer drugs.
This role also provides an exciting opportunity to work with late stage clinical data to discover new hypothesis for mechanisms of resistance and work with experimentalists to test these hypotheses in preclinical models. The scientist is expected to contribute to the development of novel methods for integrative analysis and biological interpretation of high-dimensional molecular data. The successful candidate should have a strong biological and computational background with proven capability of solving complex problems by creating innovative analytical solutions.
Collaborate with bench scientists to design and execute computational analysis of large-scale molecular data from preclinical research.
Collaborate with translational oncologists on analysis of early stage clinical trials molecular data.
Conduct in silico analysis to help address questions such as predictive biomarker, tumor indication, drug combination and resistance mechanisms.
Process, analyze and interpret high dimensional data from diverse OMICS platforms.
Contribute to the development of data packages supporting decision making.
Actively participate in project teams with multidisciplinary backgrounds to formulate data-driven, actionable hypotheses.
Devise and leverage state of the art computational approaches for oncology target identification and precision medicine.
Contribute effectively to a shared codebase that can be leveraged broadly for multiple applications.
PhD or equivalent in computational biology, genomics or a related field.
Strong background in integrative cancer biology analysis and biostatistics/machine learning methods.
Deep knowledge of high throughput molecular profiling and experience in mining "big OMICS data".
Track record of innovative and proactive problem solving, preferably in cancer biology and medicine.
Proficiency in scientific programming languages (R, Python) in UNIX/LINUX environment and algorithm development.
Ability to multi-task, effectively communicate (oral and written) and work with diverse expertise teams.
Postdoctoral research experience in Cancer Biology
Experience in productive collaboration with bench and/or translational scientists is highly desirable.
Experience analyzing single cell sequencing data is a plus.
Other Job Details
Eligible for Relocation Package
Eligible for Employee Referral Bonus
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Research and Development