Scientist 3, Genomic Technology, Oncology

Genentech

South San Francisco, CA, US
Base: $103,400 to $192,000; bonus/equity: discreti...
Multimodal single-cell genomics analysis
Computational workflows for single-cell data
Cancer cell biology experimental techniques
The Scientist will lead analysis and biological interpretation of multimodal single-cell genomics and epigenomics datasets to elucidate tumor suppressor protein roles in cancer

Job Summary

  • The Scientist will lead analysis and biological interpretation of multimodal single-cell genomics and epigenomics datasets to elucidate tumor suppressor protein roles in cancer.
  • This role involves close collaboration with wet-lab, bioinformatics, and AI/ML colleagues to translate mechanistic insights into target and biomarker hypotheses.
  • Relocation benefits are available and the position offers a competitive salary range with potential discretionary annual bonus and comprehensive benefits.

Matching Summary

The Scientist will lead analysis and biological interpretation of multimodal single-cell genomics and epigenomics datasets to elucidate tumor suppressor protein roles in cancer.

Salary

Base: $103,400 to $192,000; Bonus/Equity: discretionary annual bonus; Benefits: detailed benefits available

Skills & Requirements

Must-have

  • multimodal single-cell genomics analysis
  • computational workflows for single-cell data
  • cancer cell biology experimental techniques
  • single-cell profiling and multiomics expertise
  • integration of transcriptomic and epigenomic data
  • collaboration with bioinformatics and AI/ML teams

Nice-to-have

  • experience with cancer epigenetics
  • functional genomics with perturbation screens
  • scientific leadership and mentoring
  • strong communication skills
  • cross-functional project management
  • knowledge of chromatin remodeling and enhancer biology

Key Requirements

  • PhD in relevant biological or computational discipline
  • 4+ years academic or industry experience post-PhD
  • deep knowledge of tumor suppressor protein biology
  • hands-on expertise in single-cell profiling or multiomics
  • strong computational skills in Python and/or R
  • experience in mammalian cell culture and NGS workflows

Work Rights

Not specified

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