Postdoctoral Researcher in Computer Vision

Job summary

This position involves conducting research in computer vision, focusing on the segmentation and quantification of 3D micro-CT data related to natural heritage specimens. The role is part of an interdisciplinary project aimed at developing automated imaging systems for digitizing large collections of natural history samples.

Qualifications

• PhD in computer vision, with a focus on segmentation and/or quantification of micro-CT data.
• Experience in developing deep learning-based image analysis methods.
• Proficiency in scientific Python programming.
• Ability to handle both simulated and large real datasets.
• Strong communication skills in English, both spoken and written.
• Collaborative mindset and self-driven work ethic.

Responsibilities

• Develop new segmentation methods for large-scale micro-CT data analysis.
• Validate methods for efficient human-in-the-loop segmentation of CT images.
• Investigate self-supervised foundation models for segmentation with limited labels.
• Create reference benchmark datasets for natural heritage.
• Collaborate with experts in natural heritage and evolutionary biology.
• Contribute to open-source scientific software communities.
• Publish research findings in collaboration with colleagues.

Education

• A PhD degree (or equivalent) is required, with a statement confirming expected completion if nearing graduation.

Tools

• Experience with imaging software and tools related to computer vision and data analysis.