AbbVie Inc.
Location
South San Francisco, CA | United States
Job description
The Genomic Research Center Oncology Bioinformatics group at AbbVie Bay Area is seeking a highly motivated computational biologist to play an integral role in a multi-disciplinary team focused on developing new therapies and approaches for cancer treatment. AbbVie’s GRC is a center of excellence for bioinformatics, functional genomics, human genetics and pharmacogenomics. The GRC works across all R&D including discovery and clinical development, and multiple areas such as process sciences, global epidemiology, search and evaluation, and corporate strategy.
Based at AbbVie’s brand-new CA headquarters located in South San Francisco, CA, we have an exciting opportunity in the team as the computational oncology lead for AbbVie’s rapidly expanding, enterprise-critical, antibody-drug conjugate (ADC) platform. The candidate will be responsible for interrogating of large-scale data for target, mechanism of action, and biomarker insights; facilitating preclinical experimental design and interpretation, and formulating a data-driven foundation for patient and indication selection strategy of ADC platform in clinic.
We value novel, unique omics data as critical to AbbVie Oncology’s target identification, evaluation, and validation success. Therefore, the successful candidate will drive the ADC cancer data science framework towards AbbVie’s proprietary oncology omics and phenotyping data assets, including patient derived in vivo model, clinical samples, and real-world genomics. The candidate will be a significant contributor to such highly visible effort and interface with cross-functional ADC project teams including AbbVie genomics research community, oncology target discovery, precision medicine, and clinical development.
Key responsibilities include:
· Lead Oncology Bioinformatics efforts to enable critical data input and impact decision-making of advancing AbbVie’s antibody-drug conjugate platform
· A key contributor in establishing and executing computational strategy leveraging proprietary multi-modal, pre-clinical and human derived cancer omics data assets for target and biomarker discovery
· Support and/or expand Companion Diagnostics (CDx) development to enable precision oncology strategy for ADC programs
· Responsible for formulating scientific questions into coherent analytical efforts, developing rigorous statistical and machine learning methods, and communicating scientific findings to internal and external stakeholders
· Design novel omics profiling on pre-clinical models and patient tumor samples, and generate insights for ADC target identification and validation through omics-analysis.
· Contribute to presentations at external scientific conferences, publications in peer-reviewed journals, and regulatory filings
· Provide expertise and technical consultation for external collaborations / partnerships in academia and industry
Basic Qualifications:
· PhD, or MS in bioinformatics, statistics, mathematics, computer science, computational biology, genomics or a related field with typically 0+ (PhD), 5+ (MS) years of working experience
· Proficient in at least one general purpose programming/data science languages including but not limited to R, Python, Julia.
· Experience with common NGS data processing tools, statistical analysis, and machine learning.
· Understanding of cancer genetics and experience in analyzing multi-modal patient derived tumor genomics data
· Understanding of cancer biology
· Project experience in leveraging data science best practice tools: version control, collaborative analysis and documentation
· Strong communication skills to foster collaboration in cross-functional teams
Preferred:
· Prior experience with machine-learning based integrative analysis of genomics with proteomics, histomics, or other omics modality
· Experience with liquid biopsy omics profiling and analysis on cancer patient samples
· Experience with omics biomarker discovery and validation
· Familiarity with assay technologies and algorithm principles related epigenetic sequencing (ATAC-seq, methylation, etc.)
· Understand how to use and leverage containers for deploying standard NGS pipelines (Docker, AWS Container, etc.)
· Creates a learning environment, open to suggestions and experimentation for improvement.
AbbVie is committed to operating with integrity, driving innovation, transforming lives, serving our community, and embracing diversity and inclusion. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.
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