9 algorithm-development-"Prof"-"Prof" PhD positions at Norwegian University of Life Sciences (NMBU)
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candidate will contribute to: Developing supervised deep learning algorithms for 3D point clouds Developing self-supervised deep learning algorithms for 3Dpoint clouds Expand for a wider variety of downstream
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contribute to: Developing supervised deep learning algorithms for 3D point clouds Developing self-supervised deep learning algorithms for 3Dpoint clouds Expand for a wider variety of downstream tasks focused
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on deadwood proportion, decay stages, and forest succession. This position offers hands‑on methodological development, opportunities to publish, and collaboration within a dynamic international research
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characterize forest structure. Remote sensing data, such as images, lidar, and photogrammetric point clouds acquired from drones, aircraft, and satellites, will play a central role in the development
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photogrammetric point clouds acquired from drones, aircraft, and satellites, will play a central role in the development of the methodology. The use of new methods and new technology is a key component of the
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to improved animal welfare, reduced antibiotic use, and a more sustainable pig production. The PhD candidate will play a central role in the project, from laboratory method development to field sampling in pig
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and aims to develop a novel electromembrane process of ion separation for recovery of rare earth elements and removal of micropollutants from water. The central scientific question of the TIES project
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, develop strong analytical skills, and collaborate with international researchers in macroecology and climate change biology. The candidate will also contribute to a growing field at the intersection
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protein design to create and refine metalloprotein scaffolds; express and purify variants; integrate experimental feedback to iterate designs. Activity & structure. Develop robust assays, quantify kinetics