9 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"CNRS-" PhD positions 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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conducted according to national guidelines for University and Technical College PhD scholars, and in accordance with the Civil Servant Act, the Security Act, and the Export Control Act. Interested in learning
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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