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) at Norwegian University of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no
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of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no ), a center for
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) Positions PhD Positions Country Norway Application Deadline 13 Nov 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position PhD project: Intra-body Semantic Communication
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» Communication technology Physics » Optics Physics » Applied physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 20 Nov 2025 - 23:59 (Europe/Oslo
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continuously and precisely sense and process molecular signals among infectious bacteria colonies for diagnosis. The receiver development will consider novel design principles combining approaches in biosensors
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9th November 2025 Languages English Norsk Bokmål English English PhD Scholarship - Deep learning for forest point clouds Apply for this job See advertisement Key Information The position is part of
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accurate information. Machine learning allows for the systematization and processing of this data into new forms of information to support the management of forest resources and ecosystems. The PhD candidate
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Espen Eidum 20th November 2025 Languages English Norsk Bokmål English English Faculty of Engineering Science and Technology PhD fellow in experimental optics on the attenuation of Arctic weather
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Required qualifications PhD within forest sciences, remote sensing, data science or related field Competence in data processing and analysis of remotely sensed data Experience in use of remotely sensed data