Genentech

Genentech

Postdoctoral Fellow – Imaging Technology and Compound Screening, Regev & Singh Labs

South San Francisco

Sponsorship not specified$100k-$107kDetected 6 days ago
PythonMachine LearningBioinformaticsMicroscopyResearchCommunicationMentoring

About the role

  • Collaborative Research: Collaborate productively with experimental and computational scientists across departments, present your work to project teams, and contribute to high-impact scientific publications.
  • Professional Development: Join the Genentech postdoctoral training program, which provides an outstanding environment and the opportunity to pursue fundamental scientific questions while building methods that drive breakthrough discoveries in drug development.

Responsibilities

  • Develop and optimize high-plex imaging assays that capture rich, multiplexed readouts of cell state and morphology.
  • Develop computational approaches that expand the information extracted from each sample and improve the efficiency and quality of imaging-based measurements.
  • Design and execute large-scale compound screens across diverse, disease-relevant model systems, generating systematic, multimodal readouts of cellular response.
  • Apply single-cell and multi-omics style analyses to build maps of perturbation relationships and to prioritize the most promising compounds for a given function or activity.
  • Leverage laboratory automation and high-throughput workflows to iteratively design, run, and learn from screens at scale.
  • Collaborate productively with experimental and computational scientists across departments, present your work to project teams, and contribute to high-impact scientific publications.
  • Join the Genentech postdoctoral training program, which provides an outstanding environment and the opportunity to pursue fundamental scientific questions while building methods that drive breakthrough discoveries in drug development.
  • High-Plex Assay Development: Develop and optimize high-plex imaging assays that capture rich, multiplexed readouts of cell state and morphology.
  • Computational Methods: Develop computational approaches that expand the information extracted from each sample and improve the efficiency and quality of imaging-based measurements.
  • Large-Scale Screening: Design and execute large-scale compound screens across diverse, disease-relevant model systems, generating systematic, multimodal readouts of cellular response.

Requirements

  • Ph.D. with a proven track record of excellence in single-cell genomics, imaging, bioengineering, biophysics, quantitative biology, or a related field, with hands-on experimental expertise.
  • Must have advanced at least one key research project as evidenced by a first-author paper published or accepted in a leading peer-reviewed journal.

Nice to have

  • Experience with AI/ML applied to imaging or other high-dimensional biological data.
  • Experience with laboratory automation, liquid handling, and high-throughput experimental workflows.
  • Experience analyzing large-scale perturbation datasets and integrating multimodal data..
  • Elevate your research career to new heights with Genentech's Postdoctoral Program!
  • Join a prestigious community of early career scientists and kick-start your journey to becoming a scientific leader in biotechnology and bioengineering.
  • With competitive salaries and fully funded research expenses, you can dedicate yourself to groundbreaking research aligned with Genentech's strategic ambitions.
  • The Genentech Postdoc Program (http://careers.gene.com/us/en/students-postdocs) provides access to world-class seminars, professional development workshops, and networking opportunities.
  • Genentech is an equal opportunity employer.

Compensation

  • The expected salary range for this position based on the primary location of South San Francisco, California is $100,000 to $106,500.

Benefits

  • To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come.

This listing is sourced directly from Genentech's careers page and normalized into a canonical job model.