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Postdoc in Computer Vision for AI-based Segmentation and Quantification 3D micro-CT data for Natural Heritage
Summary by AIEngineer.careers
Postdoc in Computer Vision for AI-based Segmentation and Quantification 3D micro-CT data for Natural Heritage is a Computer Vision Engineer role (full-time). with Technical University of Denmark (DTU). in KONGENS LYNGBY, DK. Imported listing (source: miccai.org). Apply on the employer's site (miccai.org).
Imported listing (source: miccai.org) · Apply on miccai.org
KONGENS LYNGBY · DK
—
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from miccai.org
The Technical University of Denmark is seeking a Postdoctoral Researcher to advance computer vision and deep learning techniques for 3D micro-CT image segmentation and quantification. This role focuses on developing AI-driven methods to digitize and analyze natural heritage samples using robotic imaging systems. The successful candidate will contribute to cutting-edge research at the intersection of AI, scientific computing, and cultural preservation.
Responsibilities
- Develop advanced segmentation and analysis algorithms for 3D micro-CT data
- Implement deep learning models for scientific imaging applications
- Collaborate on robotic micro-CT system integration and data processing
- Publish research findings and contribute to academic projects
Requirements
- PhD in Computer Vision, Machine Learning, or a related field
- Strong programming skills in Python
- Proven experience with deep learning frameworks and scientific imaging data
- Track record of peer-reviewed publications in relevant domains
Nice to Have
- Experience with 3D reconstruction or volumetric data processing
- Background in heritage science or medical/scientific imaging
Technical University of Denmark (DTU)
Kongens Lyngby · DK · 6000+ employees
The Technical University of Denmark (DTU) is an international elite technical university. Founded in 1829, it focuses on education, scientific advice, and innovation, resting on a foundation of world-class research in technical and natural sciences.
