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numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches
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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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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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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
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Engineering » Computer engineering Physics » Computational physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 3 Feb 2026 - 23:59 (Europe/Oslo
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, fabio.hernandez@uis.no Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/288466/phd-fellowship-in-urban-m… Requirements Research FieldArchitectureEducation LevelMaster Degree or equivalent