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Field
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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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to machine learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You
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subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied data processing
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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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should hold a Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, or a closely related field Solid background in machine learning and natural
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science » Programming Engineering » Computer engineering Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 26 Apr 2026 - 23:59 (Europe/Oslo) Country Norway Type
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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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job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This is NTNU NTNU is a
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, and human-centred computing. You will join the Vision & Human-Robot Interaction (VHR) Lab, a multidisciplinary research group working at the intersection of robotics, machine learning, and human
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Science. Commitment to undergraduate and graduate education. Demonstrated expertise in machine learning/deep learning and software development (Python; PyTorch/TensorFlow). Peer-reviewed publications and strong