Department Summary
At Genentech Research & Early Development (gRED) we have initiated an exciting journey to bring together and further strengthen our computational talent and capabilities by forming a new, central organization - gRED Computational Sciences (gCS). gCS is on a mission to partner across the organization to realize the potential of data, technology and computational approaches that will revolutionize how targets and therapeutics are discovered and developed, ultimately enabling novel treatments for patients across the world. We stand at the beginning of this exciting journey.
This position will be hosted by Computational Biology for Immunology and Regenerative Medicine, with co-mentorship from the Biostatistics group within the Computational Biology & Translation department.
This internship position is located in South San Francisco, CA, on-site.
The Opportunity
We are searching for a motivated summer intern to work on Bayesian machine learning models to infer gene regulatory networks from single-cell multiome data. The focus of the internship will be on quantifying uncertainty of the fitted gene regulatory networks, and assessing the accuracy and calibration of these uncertainty estimates.
Program Highlights
Intensive 12-weeks full-time (40 hours per week) paid internship.
Program start dates are in May/June (Summer)
A stipend, based on location, will be provided to help alleviate costs associated with the internship.
Ownership of challenging and impactful business-critical projects.
Work with some of the most talented people in the biotechnology industry.
Who You Are (Required)
Required Education: Must be pursuing a PhD (enrolled student).Required Majors: Statistics, Biostatistics, Computer Science, Computational Biology or related fields.
Required Skills:
Knowledge of statistical uncertainty quantification, especially in Bayesian or Empirical Bayes contexts (e.g. credible intervals, local false sign rates).
Knowledge of modern Bayesian machine learning methods such as variational inference. Experience with these methods in single cell contexts (e.g. scVI) is a plus.
Experience with single-cell analysis. Experience with multiomic single-cell data in particular (RNA+ATAC) is a plus.
Proficiency in Python
Preferred Knowledge, Skills, and Qualifications
Excellent communication, collaboration, and interpersonal skills.
Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.
Relocation benefits are not available for this job posting.
The expected salary range for this position based on the primary location of California is $41-$45 hour. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.
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Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.