2027 Spring Intern - OpRegen Machine Learning

The OpRegen ML team develops machine learning tools that help us understand the biology behind the OpRegen manufacturing process and give our teams objective, quantitative metrics where today we rely on infrequent and subjective observation. OpRegen is an allogeneic hESC-derived cell therapy in development for geographic atrophy (advanced dry AMD), manufactured through hESC expansion, RPE differentiation, and RPE expansion. We're building ML models to capture cell morphology from routine microscopy images, non-invasively and at scale. This internship position is located in South San Francisco, on-site.

This internship centers on our in-house morphology capability, a platform we call Cellestial. The core opportunity is to turn generated imaging data into insight - running our models across the images and exploring the results for correlations with phenotypic properties - and to help extend the capability further. The intern will work closely with our computational team and with the wet-lab, Process Development, and gRED scientists who generate the data and act on the results. This internship offers the opportunity to shape the specifics around the intern's strengths and interests, anchored to the core deliverable of analyzing the already obtained images. Data analysis and insight - exploring the imaging data for correlations between morphological features and phenotypic properties, and reporting the findings Model deployment and automation - helping automate inference on new data using our compute infrastructure, so results are generated as data arrives Visualization and tooling - building tools to explore results and connect them back to their experimental context Translation to the process - working with our lab, Process Development, and manufacturing partners to identify the metrics that matter most Applied research - collaborating with research scientists on questions the morphology data can help answer Data annotation and modeling - annotating additional imaging data and contributing to related model work Program Highlights Intensive 6 months, full-time (40 hours per week) paid internship. Program start dates are in January 2027 (Spring). 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.

(Required)  Required Education You meet one of the following criteria: Must be pursuing or have attained an Associate's Degree. Must be pursuing a Bachelor's Degree (enrolled student). Must have attained a Bachelor's Degree (not currently enrolled in a graduate program). Must be pursuing a Master's Degree (enrolled student). Must have attained a Master's Degree. Required Majors: Any quantitative or engineering discipline, such as computer science, data science, biomedical engineering, computational biology or physics.

A solid understanding of machine learning and deep learning fundamentals, with substantial hands-on experience required. Strong Python, and comfortable working in a complex and mature codebase and a shared Git repository. Genuine strength in at least one of: computer vision, statistics and data analysis, software engineering and MLOps, or data visualization and tooling. Curious, coachable, and able to work independently, comfortable with some ambiguity and with helping shape their own work.   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. Image analysis. PyTorch. High-performance computing (SLURM). Relocation benefits are not available for this job posting.  The expected salary range for this position based on the primary location