18 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" PhD scholarships at Norwegian University of Life Sciences (NMBU)
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inventories and provision of environmental information. Similarly, the developments in AI and machine learning allow for new and improved processing of remotely sensed data supporting precision forestry
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Digital Twin for façade condition, fire safety risk classification, and maintenance planning Apply statistical and machine-learning methods to link climatic loads to degradation indicators Validate models
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shelf lives, and additionally may change colour, texture, and stiffness rapidly. Further, the lack of standardised 3D models for the wide variety of products makes offline learning challenging. As a
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for admission to a PhD programme at NMBU. The applicant must have an academically relevant education corresponding to a five-year master’s degree with a learning outcome corresponding to the descriptions in
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at NMBU. The applicant must have an academically relevant education corresponding to a five-year master’s degree, with a learning outcome corresponding to the descriptions in the Norwegian
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must have an academically relevant education corresponding to a five-year master’s degree or a cand.med.vet. (veterinary) degree, with a learning outcome corresponding to the descriptions in
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-year master’s degree or a cand.med.vet. degree, with a learning outcome corresponding to the descriptions in the Norwegian Qualification Framework, second cycle. The applicant must have a documented
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both NMBU and NTNU. The applicant must have an academically relevant education corresponding to a five-year master’s degree, with a learning outcome corresponding to the descriptions in the Norwegian