Computational Biologist II, CellxState

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.

The Team Through our multi-dimensional imaging program, we build imaging tools that capture life across scales — from single proteins to whole organisms — revealing how proteins and cells function, communicate, and assemble into living systems. These observations are laying the groundwork for a new generation of AI models that can predict cellular behavior and guide the development of better treatments for widespread diseases. You can learn more about our work here .

Our work brings together three powerhouse universities - Stanford, UC Berkeley, and UC San Francisco - into a single collaborative technology and discovery engine. Our Vision Pursue large scientific challenges that cannot be pursued in conventional environments Enable individual investigators to pursue their riskiest and most innovative ideas Facilitate research by scientists and clinicians at our home institutions and beyond We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease. The Opportunity Part of the Imaging Grand Challenge, The CELLxSTATE Program builds next-generation technologies to decode and control how cells make decisions — combining live-cell imaging, multi-omics, and AI at unprecedented scale.

org/ ). org/leonetti/publications/ ). At the core of our current efforts is multiDPS (Multimodal Dynamic Pooled Screening), a high-throughput platform that integrates custom microscopy, automation, CRISPR screening and molecular profiling to map and predict dynamic cell states.

We are seeking a Computational Biologist to help lead image analysis for our next-generation Optical Pooled Screening program. This is a great opportunity for candidates with a strong interest in data science, engineering, and cell biology, supported by experts in a highly collaborative and well-funded scientific environment. We embrace team science and our projects bring together biologists, technology developers, engineers, data scientists, and AI/ML experts.

What You'Ll Do

Design, develop, and maintain scalable image analysis pipelines for large-scale fluorescent microscopy datasets, with an emphasis on image quality robustness and computational efficiency. , spatial transcriptomics) into unified, AI-ready datasets that support downstream modeling and discovery. , segmentation, tracking, image-stitching, and image registration).

Partner closely with biologists and automation engineers to implement end-to-end quality control metrics, ensuring the fidelity of our experimental and computational pipelines. Architect modular and reusable processing frameworks that can flexibly support multiple experiment types within a shared infrastructure. , GitHub).

What You'll Bring PhD in Computational Biology, Biology, or Computer Science, or a MS with relevant job experience. At least 4 years of experience in Python-based image analysis or scientific computing.