Postdoc in Computer Vision for AI-based Segmentation and Quantification 3D micro-CT data for Natural Heritage - DTU Compute

Opportunity summary

Are you excited about scientific AI and developing efficient computer vision methods for analysis of complex 3D scans of natural heritage samples? Join our interdisciplinary team as a postdoc to develop advanced segmentation and other analysis methods for a novel robotic micro-CT system that will transform how natural history collections are digitized and studied. You will have the opportunity to conduct high-impact research in computer vision for 3D volumetric images, contribute to widely used open-source software, collaborate with leading researchers in physics and natural history, and publish your work while helping build technology with lasting scientific impact. Responsibilities and qualifications We are looking for a highly motivated early-career researcher in advanced image segmentation methods to join our imaging research group and project “Natural Heritage 3D”. This collaborative project between Visual Computing @ DTU Compute, DTU Physics, Copenhagen University, and the Natural History Museum aims to develop a fully automated robotic computed tomography system along with computational methods to enable 3D digitization of large collections of natural history specimens. The Natural History Museum has millions of natural specimens collected over 400 years, which provide an enormous source of information on natural history1 …

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