Data Scientist, AI for Biomedical Imaging

What you'll do

• Partner with wet-lab scientists to define imaging-analysis strategies, identify valuable AI applications, and communicate methods and results.
• Develop, validate, benchmark, and deploy image-analysis algorithms for biological phenotyping across high-throughput imaging data.
• Build scalable, reusable workflows with data science, engineering, and platform teams.

What they ask for

• PhD in computer science, AI, machine learning, biomedical image analysis, computational imaging, data science, or a related quantitative field.
• 3+ years of applied experience in AI for bioimaging and computer vision.
• Demonstrated experience developing and validating image-analysis algorithms for biological, biomedical, or pharmaceutical research.
• Proficiency in Python and the scientific deep learning stack, plus experience with image-analysis tools and Linux-based HPC, cloud, or large-scale processing environments.

Nice to have

• Experience with foundation models, self-supervised or multimodal learning, or embedding-based biological image analysis.
• Familiarity with drug discovery, phenotypic screening, or pharmaceutical research processes.

Pay

$126,000 and $234,000 USD annually (base salary); $138,600 and $257,400 USD annually (base salary)

Tools

Python, PyTorch, Hugging Face, Lightning, MONAI, scikit-image, OpenCV, OME-Zarr

AI focus

Applies deep learning, vision foundation models, representation learning, segmentation, classification, and multimodal integration to biomedical imaging and drug discovery.