145 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships in Norway
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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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that the PhD candidates complete their degrees within the nominal length of study an attractive and good learning environment for PhD candidates The programme offers several courses and candidates from other
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with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. University of Bristol (UK): To learn mathematical modelling of hormone rhythm
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and solutions that can change everyday life. Department of Structural Engineering We teach mechanical engineering, engineering and ICT, and civil and environmental engineering. The Department conducts
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a doctoral degree (PhD), the candidate is expected to: demonstrate strong motivation, curiosity, and a learning-oriented mindset work independently, take initiative, and maintain good structure and
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characteristics To complete a doctoral degree (PhD), the candidate is expected to: demonstrate strong motivation, curiosity, and a learning-oriented mindset work independently, take initiative, and maintain good
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on the success of the group, and willing to work in a multi-disciplinary team, where professional level range from students to professors, and the will to learn from, and recognize skills from all team
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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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critically and will work both independently and collaboratively within the project consortium. You should enjoy interdisciplinary research and take keen interest in learning and working as part of
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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
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in English Solid knowledge in finite element analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks