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develop models suited to monitoring the marine environment. The position is in the Digital Signal Processing and Image Analysis (DSB) research group, Section for Machine Learning, Department of Informatics
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4 Sep 2025 Job Information Organisation/Company Instituto Pedro Nunes Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions
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: • Backend based on REST/GraphQL APIs that expose cork stopper catalogue functionalities, creation and management of final products, and consultation of machine learning model records; • Angular frontend
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to treatment, population health monitoring, workforce development and leadership, policy, and advocacy. Background The Robotics, Autonomy and Machine Intelligence (RAMI) Group led by Prof Nabil Aouf is dedicated
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optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive
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. Given their importance, continuous monitoring and fault diagnostics are crucial—especially as machine learning algorithms play an increasingly prominent role in predictive maintenance and reliability
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of these features for distinguishing attacks from normal behaviour, through statistical and/or machine learning-based analysis. • Analyse the applicability and potential adaptation of these features for anomaly
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status, domestic violence victim status, caregiver status, military status, including past, current, or prospective service in the uniformed services, social class, or any other category or characteristic
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: neuromorphic algorithms, machine learning, classifier development, AI programming Key tasks include experimental and/or computational research, collaboration within the project team, publishing results in high
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language requirement of the UK HEI; Have a background or a proven interest in AI foundations and its application in civil and environmental engineering, including machine learning, sustainable construction, climate