25 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" PhD scholarships in Norway
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to research, development and demonstration of a methodology for building and integrating machine learning solutions for past technical artefacts. Contributing to the development of holistic view of product
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health, epidemiology, statistics, biostatistics, or machine learning/artificial intelligence. You must have a strong academic background from your previous studies and have an average grade from your
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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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systems to reason more coherently about ship designs, reducing ambiguity in the data available to machine‑learning systems, and supports explainability by grounding AI outputs in a known structure. This
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selection criteria Experience with machine learning or other relevant AI technologies Experience with condition monitoring, preferably within maritime domains Knowledge of ship machinery and systems Good oral
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promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research
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(ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning
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Computer science Engineering » Computer engineering Technology » Information technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 10 Feb 2026 - 23:59 (Europe/Oslo
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, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning, the project will make use of historical radar
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must have documented experience with hydrogen technologies, in particular liquid hydrogen systems, hydrogen storage, or cryogenic energy applications. You must have experience with data analysis, machine