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14 Jul 2026 Job Information Organisation/Company FEUP Department Human Resources Division Research Field Engineering » Computer engineering Engineering » Other Researcher Profile First Stage
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, machine learning, and statistical methods for time-series forecasting in the electricity sector, including demand, renewable generation, and market prices. Development and evaluation of point and
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 months ago
. The successful candidate will be expected to carry out the following scientific activities: Application of advanced Machine Learning, Deep Learning, reduced-order modelling, and physics-informed/-guided modelling
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machine learning). Minimum requirements: Average grade of 18 in the Master Degree in Industrial Engineering and Management. Proficiency in Portuguese and English. 5. EVALUATION OF APPLICATIONS AND SELECTION
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; - Development of a simulation module for parcel delivery operations, integrating traditional simulation techniques with Machine Learning models; - Development of algorithms for the integration of Machine Learning
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knowledge of machine learning models and Python tools for signal processing and machine learning. General knowledge of system architecture and APIs. Previous knowledge of physiological signal processing. 5
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of physiological signals (pre-processing, filtering, feature extraction in the time, frequency, and time-frequency domains). Development and validation of machine learning and deep learning models integration and
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-processing, filtering, feature extraction in the time, frequency, and time-frequency domains). Development and validation of machine learning and deep learning models integration and analysis of data from
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). Development and validation of machine learning models for calculating occupational health indicators. Integration, management, and analysis of data from wearable monitoring devices. Experimental evaluation
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models to characterize lung cancer based on a non-invasive methodology. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning