200 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" scholarships in Norway
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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Oslo
- Norwegian University of Life Sciences (NMBU)
- University of Stavanger
- UiT The Arctic University of Norway
- University of Bergen
- OsloMet
- Molde University College
- University of South-Eastern Norway
- Western Norway University of Applied Sciences
- BI Norwegian Business School
- CICERO Center for International Climate Research
- NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
- Nansen Environmental and Remote Sensing Center
- Nature Careers
- OsloMet – Oslo Metropolitan University
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- Østfold University College
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research disciplines. For further information about the different research disciplines see https://www.ntnu.edu/imf/research . Are you motivated to take a step towards a doctorate and open exciting career
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information can be found here: https://www.ntnu.edu/mai Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within the framework described above
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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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is internationally recognized, with interests spanning a broad range of areas - including statistical machine learning, high-dimensional data and big data, computationally intensive inference
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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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Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions. As
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optimization (WOB, RPM, flow rate, etc.) using machine learning techniques Anomaly detection for downhole vibrations, bit failure, and circulation losses Integrating physical modeling, digital twins, and data
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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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of data analytics, machine learning or artificial intelligence methods is desirable. Personal qualities Strong ability to follow through on tasks and projects Motivation for the academic and research field
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will utilize economic theory, simulation, economic evaluation and machine learning to quantify the benefits of advanced diagnostic technologies in reducing overdiagnosis. Competence You must have