AI Biologist - Microscopy
Position Title:
AI Biologist - Microscopy Work Location: San Francisco or Remote Assignment Duration: FTE role Work Arrangement: San Francisco or Remote
Position Summary:
Our organization builds rigorous scientific benchmarks (benchmarks.bio) for AI agents across biology. We work with frontier labs and pharma to measure whether agents can handle real biological workflows: the messy, multi-layer reasoning that matters in the field. Background & Context: We’re seeking an AI Biologist to join our Microscopy team, pushing what AI can achieve in biological imaging.
Key Responsibilities:
- Define what expert reasoning looks like for an imaging question, and write gold-standard answers with the rationale an experienced microscopist or pathologist would defend
- Design realistic scenarios across the imaging workflow: sample prep, staining, acquisition, preprocessing, segmentation, quantification, and interpretation
- Curate image datasets across modalities: immunofluorescence, confocal and live-cell, electron microscopy, histology and histopathology, and high-content screening
- Build analysis pipelines in Python, including deep-learning segmentation, that produce verifiable ground truth
- Partner with software engineers to turn your judgment into new workflows
- Test whether agents distinguish true signal from artifact, such as bleed-through, uneven illumination, fixation damage, out-of-focus planes, or segmentation failure
- Adjudicate ambiguous images: decide what the data supports, where reasonable experts would disagree, and which additional stain, image, or experiment would settle the call
- Test whether agents choose the right imaging modality, resolution, and unit of analysis for the question
- Interrogate agent reasoning step by step, and challenge conclusions that sound right but would not survive pathologist review or lab meeting
- Pinpoint where agents go wrong: why a step fails, what an expert would do instead, and what evidence would change the call
- Score agent confidence, rewarding explicit uncertainty over overconfident calls on ambiguous images
- Qualification & Experience:
- PhD in cell biology, bioimage analysis, pathology, or a related field; or an MD with pathology training
- Senior, hands-on imaging experience: you have looked at thousands of samples and know what normal and abnormal look like
- Direct experience with image segmentation tools such as Cell
- Profiler, Cellpose, StarDist, QuPath, ilastik, napari, or FijiDeep expertise in at least one area (bioimage analysis, cell biology, or histopathology) and working fluency across the others
- Strong command of experimental design, image quantification, and statisticsAI-ready from day one: daily use of Claude, Cursor, or similar agents, with the judgment to spot where model reasoning is technically correct but scientifically unsound
- Confidence to overrule an AI agent when the evidence demands it, and the openness to update when shown wrong
- Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary calls
Bonus:
electron microscopy, pathology, or pharmacology experience (e.g., pharmacodynamic or drug-uptake imaging assays)
Bonus:
familiarity with public resources such as the Image Data Resource (IDR), BioImage Archive, Human Protein Atlas, Cell Painting Gallery, or TCGA whole-slide images Applicant Notices & Disclaimers For information on benefits, equal opportunity employment, and location-specific applicant notices, click here