46 phd-studenship-in-computer-vision-and-machine-learning PhD positions at NTNU Norwegian University of Science and Technology
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the position takes place from 1 August 2025. For employment as a PhD candidate, it is a prerequisite that you gain admission to the PhD programme in Electric Power Engineering within three months of your
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combined with Computation Fluid Dynamics (CFD) within this topic. As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a
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system operation in the near future? The PhD position will pursue the following overall objectives: Contribute to the definition and vision of smart grid resilience Develop and evaluate modern methods
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prerequisite that you gain admission to the PhD programme in Electric Power Engineering within three months of your employment contract start date, and that you participate in an organized doctoral programme
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Environmental Engineering at NTNU has a vacancy for a PhD candidate position focusing on Value Delivery Analysis in Megaprojects. The research is associated with the research program Bedre megaprosjekter (Better
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in higher education and research, in and outside academia. A PhD fellowship is available at the Department of Computer Science on the topic of Interaction Design. Your immediate leader will be the unit
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. If you have a weaker grade background, you may be considered if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the PhD Program in
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for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme You must have good written and oral English language skill
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Doctoral Programme (https://www.ntnu.edu/nv/phd ) Good oral and written presentation skills in Norwegian or another Scandinavian language equivalent to level A2 Hands on experience with relevant
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Excellent English skills (written and oral) Excellent computer programming skills Preferred qualifications (documentation required) Knowledge and skills in the following areas are highly relevant: estimation