Computational Biologist II, CellxState
About The Position
Biohub is a 501(c)(3) biomedical research organization building the first large-scale scientific initiative combining frontier AI with frontier biology to solve disease. We build the technology to help scientists around the world use AI-powered biology to study how cells operate, organize, and work as part of systems to understand why disease happens and how to correct it. With our compute capacity, AI research and engineering, and state-of-the-art technology for measuring, imaging, and programming biology, we are enabling scientists worldwide to use AI-powered biology to advance our understanding of human health. 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. We also create large reference datasets that can be mined and reused by the entire community for discovery, like our OpenCell project that maps protein localization and interactions (https://opencell.czbiohub.org/). Our science is fully open-source and published in journals like Science, Nature Methods, and Cell (https://biohub.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.
Requirements
- 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. Experience with fluorescence microscopy, confocal, or lightsheet is a plus.
- Fluency with computational tools and infrastructure such as Python, Github, and Slurm.
- Experience with modern biological data formats such as OME-Zarr and AnnData.
- Experience designing workflows for large, complex datasets, including scalable storage formats, and reliable metadata and experiment tracking.
- A proven track record of individual innovation, together with a strong ability to work collaboratively.
- A passion for research and understanding how cells work.
- An enthusiasm for team science and open science - this position will be embedded in a large multi-disciplinary team.
- Excellent written and oral communication skills.
Responsibilities
- Design, develop, and maintain scalable image analysis pipelines for large-scale fluorescent microscopy datasets, with an emphasis on image quality robustness and computational efficiency.
- Integrate emerging multi-modal data types (e.g., spatial transcriptomics) into unified, AI-ready datasets that support downstream modeling and discovery.
- Advance our bio-image analysis capabilities (e.g., 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.
- Publish and disseminate impactful findings through preprints, papers, and software repositories (e.g., GitHub).
Benefits
- Provides a generous employer match on employee 401(k) contributions to support planning for the future.
- Paid time off to volunteer at an organization of your choice.
- Funding for select family-forming benefits.
- Relocation support for employees who need assistance moving
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
