Full Stack Engineer — Computational Pathology Platform

DeePathology builds STUDIO, a computational pathology platform for analysing whole slide images of tissue. We work with pharma and diagnostics partners, delivering analysis applications that run on their own processing platforms.

About the role

You will build end-to-end image analysis applications: train detection and segmentation models using STUDIO's annotation and training tools, package them as containerised applications that run on our clients' platforms, analyse the outputs quantitatively, and extend STUDIO itself.

This is a part-time position and suits a strong student in computer science, biomedical or electrical engineering.

What you will do

• Train and iterate detection and segmentation models for new stains, using STUDIO's annotation and training tools - including making the annotation calls that define what the model learns, in consultation with our pathology reviewers

• Package analysis applications as Docker containers and deploy them on client processing platforms, validating that results match local runs

• Fetch detection outputs for slide cohorts through client Python SDKs; parse detection data - cell coordinates and class labels per tile

• Restrict cells to regions of interest, count by class, produce per-slide distributions and cohort aggregation, and compare results against manual reference scores

• Add features to the STUDIO application - Angular frontend, Python backend

What we look for

• Solid Python - comfortable with NumPy arrays, indexing, and coordinate transformations

• Experience training and iterating segmentation or detection models on real data (PyTorch or TensorFlow)

• Docker - building images, running containers, and understanding why a container can behave differently than a local run

• Image processing (scikit-image, OpenCV, or PIL)

• Git, and comfort working in a Linux command line

• Quantitative analysis - distributions, aggregation, comparison against a reference

Advantageous

• Angular and TypeScript, or comparable frontend framework experience

• REST API development (Flask, FastAPI, or similar)

• Whole slide imaging - pyramidal TIFF, OpenSlide, tifffile, resolution/MPP handling

• HDF5 and structured scientific data formats

• AWS - EC2, ECR, S3, and aws CLI2

• Terraform and infrastructure

• Background in biomedical engineering, life sciences, or medical imaging