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Pfizer Sr. Computational Biologist, Oncology Drug Discovery in La Jolla, California

ROLE SUMMARY

We seek a talented and highly motivated computational biologist to join a team that supports oncology drug discovery by developing and applying innovative analytical tools and methodology with a focus on multi-omics and single cell genomics. This is an exciting opportunity to make an impact at all stages of drug discovery including target identification, translational research and clinical development in a dynamic, collaborative and inter-disciplinary environment. The successful candidate will have a combination of strong computational and biological background, with proven capability of solving complex problems by creating innovative analytical solutions.

ROLE RESPONSIBILITIES

  • Develop and apply state of the art computational approaches for spatial transcriptomics, RNA-Seq, ATAC-Seq and other high-dimensional multi-omics data analyses.

  • Collaborate with experimental biologists to support technology development for transcriptomics and epigenomics profiling for application in clinical and translational research.

  • Contribute to data integration efforts and perform data mining analyses to identify novel drug targets and biomarker hypotheses and derive insights into drug resistance and mechanism of action.

  • Contribute to data analysis and publication efforts in cross-interdisciplinary clinical genomics studies that aim to elucidate drug resistance mechanisms and immune response to standard-of-care therapies.

  • Contribute to the development of pipelines and systems for data analysis, integration and management.

BASIC QUALIFICATIONS

  • PhD or equivalent in bioinformatics, computational biology or a closely related field.

  • Strong skills in scientific programming (R, Python, Perl) in UNIX/LINUX environment and algorithm development.

  • Proven record of scientific rigor and success in applying state-of-the-art computational approaches to solving biological problems, preferably in cancer biology and medicine.

  • Strong background in high-dimensional, multivariate data analysis and biostatistics/machine learning methods.

  • Demonstrated skills and experience in multi-omics data analysis (whole exome/genome sequencing, bulk-tumor and single-cell RNA-Seq), with deep knowledge of high throughput molecular profiling.

  • Ability to multi-task, effectively communicate (oral and written) and work in multidisciplinary teams.

PREFERRED QUALIFICATIONS

  • Postdoctoral or work experience in biopharmaceutical industry and academia.

  • Experience in spatial transcirptomics, epigenomics or single cell sequencing data analysis.

  • Experience in developing web-based applications and databases.

OTHER JOB DETAILS

  • Eligible for Relocation Package

  • Eligible for Employee Referral Bonus

  • #LI-PFE

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