Genomic Oncology Research Leader
2 weeks ago
At 1925 GlaxoSmithKline LLC, we are seeking a highly skilled and experienced individual to lead our team as an Associate Director of Oncology Genomics.
The successful candidate will have a key role in the analysis of large-scale somatic genomic and clinical data, applying cutting-edge algorithms and developing automated methods to support large-scale bioinformatics analysis. They will be involved in the processing and analysis of NGS data (with a focus on WES/WGS, SNVs/CNVs, ctDNA) and will need a solid understanding of computational approaches for cancer genome analysis and cancer biology to derive meaningful and reproducible biological insights.
Key Responsibilities:
- Process and analyze large-scale somatic genetic datasets (WES/WGS, SNVs, CNVs) and integrate with clinical/phenotypic datasets to derive biological insights.
- Develop automated methods to support large-scale somatic genetic, bioinformatics analyses and collaborate closely with other teams (statistical genetics/AIML) to develop advanced algorithms and models.
- Integrate complex molecular data (e.g., transcriptomics, proteomics, metabolomics) to derive insights and understand the underlying biology.
- Lead multidisciplinary teams effectively to answer complex scientific questions.
- Communicate complex ideas and concepts to a range of stakeholders, including peers and leaders.
- Collaborate with cross-functional teams to support the development and implementation of oncology genomics strategies.
- Stay up-to-date with the latest advancements and trends in oncology genomics and molecular data integration.
- Evaluate and implement new methodologies and technologies to improve the efficiency and effectiveness of data analyses.
- Foster a culture of collaboration, innovation, and continuous learning within the team.
- Ensure compliance with relevant regulations and guidelines in the field of oncology genomics.
Why You?
As a highly skilled and experienced professional, you will be responsible for leading our team in the analysis of large-scale genomic data. You will have a key role in developing automated methods to support large-scale bioinformatics analysis and will be involved in the processing and analysis of NGS data.
Basic Qualifications:
- Ph.D. in a quantitative subject, e.g., bioinformatics, biostatistics, computational biology, or epidemiology, with 8+ years of combined academic and industry experience.
- 3+ years of programming skills experience (e.g., Bash, R, Python) and bioinformatics tools (bcftools) and workflow management systems (e.g., nextflow).
- 3+ years of experience in processing and analysis of large-scale genomic datasets, genetic data analysis, including SNVs/CNVs, WES/WGS, and data interpretation through integration with clinical/phenotypic information.
- 3+ years of experience in cancer research, including a deep understanding of computational approaches for cancer genome analysis.
Preferred Qualifications:
- Proven ability to effectively lead multidisciplinary teams to answer complex scientific questions.
- Evidence of independence in leading research projects and of the ability to develop novel statistical or bioinformatics methods.
- Advantageous to have experience in complex molecular data integration, such as transcriptomics, proteomics, and metabolomics.
- Strong communication skills to convey complex ideas and concepts to a range of stakeholders.
- Excellent problem-solving and analytical skills to address complex scientific questions.
- Strong collaboration and partnership skills to work effectively with cross-functional teams.
- Excellent project management skills with a focus on delivering results.
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