Applied Computer Vision Scientist for Quantum Devices

OQC; Reading; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

OQC is seeking an Applied Scientist in Computer Vision to turn complex imaging into quantitative insights for quantum processor development. You will design end-to-end image-analysis pipelines, combining classical processing with deep learning to enable robust measurements from microscopy and metrology data.

You will work across nanofabrication and materials teams, delivering validated pipelines and maintainable software within collaborative scientific codebases.

Qualifications

• Experience with CV and image processing, including segmentation and measurement.
• Experience extracting quantitative metrics from microscopy/metrology imagery.
• Experience applying deep learning to CV tasks (classification/detection/segmentation).
• Strong Python-based computing with NumPy/SciPy/OpenCV/TensorFlow/PyTorch and Pandas.
• Experience developing maintainable Python software and automated analysis pipelines.
• Familiarity with robust software engineering practices and testing.

Responsibilities

• Design and maintain CV pipelines transforming imagery into quantitative outputs.
• Develop both classical and DL approaches for defect detection and measurement.
• Validate methods with ground truth, metrics, and error analysis.
• Collaborate with fabrication and metrology to translate questions into analysis.
• Produce reusable software within shared scientific codebases.

Skills

Classical CV

Deep learning

Python

OpenCV/Scikit-image

PyTorch

TensorFlow

Segmentation

Quantitative measurement

Software testing

Collaboration with domain experts

Tools

Docker

Kubernetes

CI/CD

Job description

OQC is seeking an Applied Scientist in Computer Vision to turn complex imaging into quantitative insights for quantum processor development. You will design end-to-end image-analysis pipelines, combining classical processing with deep learning to enable robust measurements from microscopy and metrology data.

You will work across nanofabrication and materials teams, delivering validated pipelines and maintainable software within collaborative scientific codebases.