AI Skills for Bio-Imaging & Digital Pathology Jobs
Imaging roles bring computer vision to microscopy, histopathology, and high-content screening.
From 19 live Imaging & Pathology roles, within our analysis of 462 AI/ML postings · updated August 25, 2026
What Imaging & Pathology roles actually do
You build computer-vision models for microscopy, pathology, and high-content screening: segmenting cells, classifying phenotypes, and quantifying what images reveal about biology.
Most-requested skills for Imaging & Pathology roles
Share of the 19 live Imaging & Pathology AI/ML postings mentioning each skill.
The core stack, explained
The tools that show up most in Imaging & Pathology postings, and why they matter.
Who's hiring
Companies with the most open Imaging & Pathology AI/ML roles right now.
Typical pay
Median-to-median disclosed salary band across these roles, where pay is posted.
What makes Imaging & Pathology different
This is the most computer-vision-heavy sub-field: deep learning on images, often trained on large proprietary datasets, with an emphasis on segmentation, classification, and phenotype extraction. Familiarity with how biological images are generated, and their artifacts, is a real edge over a generic vision background.
How to break into Imaging & Pathology
A vision project on real biological images (cells, tissue, or screening data), with careful handling of artifacts and labels, translates directly. Generic ImageNet-style work matters less than showing you understand microscopy or pathology data.
Frequently asked
What skills do imaging & pathology jobs require?
Across 19 live Imaging & Pathology AI/ML roles, the most-requested skills are Computer vision, Python, PyTorch, Deep learning, MLOps, TensorFlow. Percentages for each are in the breakdown above.
How is Imaging & Pathology different from general AI/ML in biotech?
This is the most computer-vision-heavy sub-field: deep learning on images, often trained on large proprietary datasets, with an emphasis on segmentation, classification, and phenotype extraction. Familiarity with how biological images are generated, and their artifacts, is a real edge over a generic vision background.
Is bio-imaging just general computer vision?
The methods overlap, but biological images have their own challenges: scale, artifacts, weak labels, and the need to tie visual features back to biology. Domain familiarity is a real differentiator.
Find Imaging & Pathology roles
Browse live imaging & pathology and related AI/ML roles at top biotech and pharma companies.
Browse all jobsPart of the AI/ML Skills in Biotech guide. Explore other sub-fields: Protein design · Drug discovery · Genomics · Clinical