All over the world, Pfizer colleagues are working together to positively impact health for everyone, everywhere. Each position at Pfizer touches and contributes to the success of our business and our world. That's why, as one of the global leaders in the biopharmaceutical industry, Pfizer is committed to seeking out inspired new talent who share our core values and mission of making the world a healthier place.
Role Description
We are looking for a Computational Biologist to drive the cancer target discovery and patient stratification efforts through analysis of large-scale datasets from functional genomics screens, genomics profiling of clinical and pre-clinical samples using diverse technologies incorporating network and pathway data. The candidate will have the opportunity to work with dedicated teams of scientists generating new data to elucidate Cancer System Biology and impact target selection and identification of patients most likely to respond to new therapies.
We are seeking an accomplished scientist with proven expertise in developing and applying network and pathway-based computational methods to analysis of diverse genome-scale data. The candidate will contribute to data-driven decisions for novel targets discovery and propose testable hypotheses for new targets and combinations validation. The candidate will also work closely with early stage development programs to identify patients’ populations most likely to benefit from new therapies and combinations. The candidate is expected to contribute to the Pfizer Oncology research mission to provide best imaginable cancer therapies for patients. Our pipeline of cancer therapeutics includes small molecules, antibody-drug conjugates and immune-oncology therapies and combinations. The candidate is expected to influence data-driven decisions from target identification and validation to generating translational hypotheses for biomarkers discovery.
Responsibilities
• Apply computational methods to integrate, visualize and interpret data resulting from Proteomic, Genomic, Next Generation Sequencing and efficacy data from pre-clinical and clinical studies.
• Work closely with teams of biologist and clinicians developing analysis approaches for systematic target and patient population identification, propose new experimental approaches and computational analysis to drive novel target and biomarker discovery.
• Establish network-based methods for omics-scale data integration and mining, drive the computational data-mining efforts for target discovery and patient selection.
• Effectively collaborate with Drug Discovery teams of cell biologists, biochemists, pharmacologists and clinicians.
• Deduce, summarize and communicate results of data mining and analysis and contribute to understanding of drug mechanism of action, target indication, patient selection strategies and identification of translational and response biomarkers.
Qualifications
Ph.D. and/or Post Doctorate training in computational biology or bio-informatics with at least 5 years industry or academic experience in a analyzing large-scale molecular data.
The ideal candidate will have demonstrated expertise in:
• Development and application of network-based methods for integration and analysis of genomics data.
• Data mining and application of systems biology approaches to large OMICS datasets.
• Analysis of the Next Generation Sequencing data including; WES, RNAseq, miRNA, Epigenetics, functional genomics and synthetic lethal screens.
• Solid programming skills in R, Perl Python, SQL etc. in LINUX/UNIX environment.
• The successful candidate should have strong organizational and interpersonal skills including excellent oral and written communication and ability to work effectively in matrix collaborative teams.
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