Scientist II, Scaling Lead

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 Biohub is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. The Biohub focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies.

Our Vision

• We pursue large scientific challenges that cannot be pursued in conventional environments
• We enable individual investigators to pursue their riskiest and most innovative ideas
• The technologies developed at the Biohub facilitate research by scientists and clinicians at our home institutions and beyond
  Diversity of thought, ideas, and perspectives are at the heart of Biohub and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution.

This position will work with the team of Dr. Loic Royer to build instruments, AI, and molecular tools to understand how cells self-organize to build, maintain, and repair tissues. The team designs and operates state-of-the-art light-sheet microscopes (including the DaXi platform), develops the Ultrack cell-tracking framework, and produces the Zebrahub atlas of vertebrate development.

Biohub is seeking a Scientist II to lead the scaling of our imaging and data-generation pipeline. This role will set throughput targets, find the bottlenecks that matter most, and work hands-on with the sample-prep, imaging, and computation teams to remove them — at the bench, at the microscope, and at the keyboard.

We are looking for someone who is curious, dependable, and excited to work at the interface of biology, imaging technology, and collaborative platform science. The ideal candidate is proactive, learns quickly, communicates well across teams, and enjoys contributing to both established workflows and the development of new experimental approaches across a wide range of disciplines, from optics, microscopy, and image processing to developmental, cell, and molecular biology.

This position is well-suited for candidates who have already built a live-imaging pipeline in a developing organism from the ground up — instrument, reporter lines, sample handling, acquisition, and analysis — and are excited to take on the challenge of scaling that pipeline. The strongest candidates will have hands-on experience in microscope design, sample preparation, model-organism husbandry, imaging, and quantitative analysis, with a track record of making methods more robust and reproducible.

• Map the full sample-to-data pipeline, define quantitative throughput and quality targets, instrument each stage with metrics and dashboards, and maintain a living view of the true bottlenecks — so effort is always spent on the binding constraint.
• Spend significant hands-on time alongside sample-prep, imaging, and computational scientists, diagnosing and fixing the concrete obstacles — protocol, hardware, software, or logistics — that limit data generation on any given week.
• Increase the number of specimens prepared and imaged per session and reduce variability across the sample-handling workflow — staging, mounting, and quality control — in partnership with the Bioengineering and Zebrafish Transgenesis platforms.
• Improve multi-specimen acquisition, instrument uptime, and cross-instrument reproducibility on the group's light-sheet microscopes, pushing sustained throughput toward the platform's practical limits.
• Work with the computation team to keep the image-processing pipeline (denoising, registration, fusion,…