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9th April 2026 Languages English Norsk Bokmål English English PhD Fellowship in Surrogate Modelling of Fluid Flows using Deep Learning Apply for this job See advertisement Job description The
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-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data frameworks. Programming languages such as e.g. Python, C++, and LABVIEW. In the assessment
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that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. Research topic This PhD project will investigate the safety and
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application development. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data
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transfer learning, data-driven calibration, or case-based reasoning, to improve decision-making, reduce uncertainty, and justify steering recommendations? This PhD research together with the DigiWells team
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the researchers from Department of Automation and Process Engineering will play a key role. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early
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26 Feb 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application
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of Visual Intelligence is to develop novel, innovative solutions based on deep learning to extract knowledge from complex image data. Deep learning, aided by machine learning techniques in general, has led
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integrated circuits (PIC). An optical set-up will be used to characterize the chips and demonstrate the capabilities of the PICs. The PhD will collaborate with researchers in machine learning for analysis
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience