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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in analyzing multi-omic and genomic data to derive oncology-specific clinical insights, while effectively communicating findings to diverse audiences. Proven ability to lead research projects and collaborate with multidisciplinary teams in the context of real-world evidence and next-generation sequencing.
Highest-signal resume keywords
PhD In Computational BiologyExperience In Multi-Omic Data AnalysisOncology-Specific Clinical InsightsProject Management SkillsMachine Learning Techniques
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Multi-Omic Data AnalysisGenomic Data AnalysisTime-To-Event MethodologiesNext-Generation SequencingClinical Insights DerivationRetrospective Database AnalysisMachine Learning TechniquesHigh-Throughput SequencingData IntegrationAnalytical Results Communication
Soft Skills
CollaborationCommunicationPresentation SkillsProject Management
Industry Keywords
Real-World EvidenceOncology GuidelinesBiomedical DatasetsResearch ProjectsFormal Presentations
About the role
Key responsibilities & impact- Lead and contribute to research projects supporting R&D and Medical Affairs initiatives
- Leverage large-scale real-world clinical and multi-omic molecular data
- Work with the Tempus Medical Sciences Team and oncology research leaders to understand goals and translate scientific questions into insights
- Present research-study insights to external research partners through formal presentations
- Communicate research findings and analytical results to audiences with varying technical and genomics expertise
- Stay updated on methodological advancements in real-world studies, next-generation sequencing, and oncology guidelines
- Participate in publications and podium activities
Requirements
What you’ll need- 1+ years experience in industry or academia following completion of a PhD degree in quantitative NGS-related disciplines (e.g. Computational Biology, Genetics, or similar)
- Alternatively, a PhD in computational biology with a strong record of multi-omic, high-throughput sequencing data analysis
- Experience deriving oncology-specific clinical insights using genomic and/or real-world data
- Experience deriving real-world endpoints using time-to-event methodologies within a retrospective database
- Excellent project management skills
- Proven ability to collaborate with multidisciplinary scientists to define and execute analysis plans using omics datasets, including genomics and transcriptomics
- Experience integrating molecular data with real-world evidence and longitudinal clinical outcomes (nice to have)
- Hands-on experience applying machine learning techniques or foundation models to complex biomedical or multi-omic datasets (nice to have)
Benefits
Comp & perks- Incentive compensation may be offered
- Restricted stock units may be offered
- Medical and other benefits depending on the position