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TRAINING: Literature review on anomaly detection in network data; Using deep learning to detect anomalies in network data flows.; 4. REQUIRED PROFILE: Admission requirements: Degree in Computer Engineering
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19 Sep 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal
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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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results. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - Develop machine learning-based models from data.; - Validate the developed models with real data.; - Publicize the work in international
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AND TRAINING: - survey and analyze the state of the art in emerging wireless networks, including simulation aspects using real data assimilation, Machine Learning, and digital twin approaches
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with simulation techniques, energy efficiency models, large-scale energy consumption data, machine learning techniques and interpretation (unsupervised); - Education, experience and research orientation
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26 Aug 2025 Job Information Organisation/Company INESC TEC Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Country Portugal Application Deadline 8
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
, with application to biomedical flows (e.g. microcirculation) it is now intended to develop an improved algorithm for advanced particle tracking using machine learning. The algorithm should be tested in
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wastewater treatment plants, with the following main objectives: 1 - Model calibration through Machine Learning methodologies using process data. 2 - Development of a multimodal online sustainability
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the direction of A/Prof Claudia Szabo in the School of Computer and Mathematical Sciences at the University of Adelaide. The project is a collaboration with Defence Science and Technology Group, within the Combat