2025 Summer Intern - Digital Pathology Image Analysis - Spatial Omics

The Department of Pathology is embedded within Genentech’s Research and Early Development Organization (gRED) and works to ensure that strategies for the treatment and cure of disease are based on accurate analyses of pathogenetic mechanisms. In addition, the department is a key driver in Genentech’s Digital Pathology and Spatial Omics efforts. The department develops cutting edge tissue technologies to support scientific discovery and collaborates with  research scientists in the discovery, characterization, and development of novel therapeutic products for a variety of human diseases. 

DPIA-SO (Digital Pathology Image Analysis-Spatial Omics) is a Research Pathology sub-team specializing in collaborative spatial omics computational analysis (Spatial Proteomics and Transcriptomics). Our mission is to provide scientists with actionable insights from high-dimensional imaging data by developing and leveraging transparent, reproducible and scalable spatial analysis methods and pipelines.

This internship position is located in South San Francisco, On site

Key Responsibilities

Perform single-cell segmentation, feature extraction, and phenotyping analysis on bright-field and immunofluorescence-stained whole slide images using advanced methodologies and algorithms

Work closely with the spatial omics analysis team to both evaluate existing methods and develop novel and robust deep-learning methods to determine cell marker positivity in spatial proteomics datasets

Provide regular updates to stakeholders

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 Education: You meet one of the following criteria:

Must be pursuing a Master's Degree (enrolled student).

Must have attained a Master's Degree.

Must be pursuing a PhD (enrolled student).

Preferred majors: Computational Biology, Bioinformatics, Mathematics, Statistics, Physics, Engineering or other related quantitative/scientific fields

Required

Experience with training, validating, and refining image-based deep-learning models.

Python coding experience.

Excellent problem-solving and critical thinking abilities.

Other Preferred Qualifications

Excellent communication, collaboration, and interpersonal skills.

Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.

Experience with digital pathology and/or bioimaging.

Experience analyzing image or spatial datasets (Spatial Transcriptomics or Proteomics).

Familiarity with common deep learning Python frameworks (i.e. Pytorch, Tensorflow, etc).

Familiarity with deep-learning architectures and usage of model zoos.

Relocation benefits are not available for this job posting. 

The expected salary for this position based on the primary location of  California is $50 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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