153 machine-learning "https:" "https:" "https:" "https:" "https:" "VIETNAMESE GERMAN UNIVERSITY" PhD scholarships in Norway
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modelling, and high-performance computing. The position offers close supervision, access to modern computational infrastructure, and collaboration opportunities across disciplines — from mechanics to machine
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for machine learning models to optimise membrane properties, structure, and fabrication. The fellow will play a key role in the experimental part of the project, including: Preparation and characterisation
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intelligence, data analytics, uncertainty analysis, probabilistic modelling, or statistical learning you have experience working on relevant research or project activities involving machine learning or data
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area on civil security by focusing on the vulnerability assessment of urban environments, sustainability, resilience, and knowledge for a better world (https://www.ntnu.edu/civil-security ). Duties
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affiliated with the Centre, and opportunities for research stays with partners, both nationally and abroad, through its international network. Read more about the Centre and its research at the website: https
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, SFI-CELECT (Research Centre for Effective Engineering and Learning in Complex Systems) . The position is 3-year doctoral research fellowships starting in 2026/2027. The PhD candidates will be embedded
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
(as machine learning techniques, etc.). Personal characteristics In the evaluation of which candidate is best qualified for the PhD position, emphasis will be placed on education, experience and
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the Norwegian State Employees Act, the Security Act, and the Export Control Act. This position is a training/educational position. Grant-funded travel abroad should be expected. Interested in learning more about
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. Interested in learning more about the position? We are happy to tell you more. Contact Associate Professor Håvard Bjørgen, phone: +47 413 66 569, e-mail: havard.bjorgen@nmbu.no or Professor Erling Olaf
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architecture. The research focus of this PhD position is the design of performant and energy-efficient Edge Artificial Intelligence (AI) accelerators. Such accelerators may be either tightly integrated with