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