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; Jorge Manuel Oliveira Henriques IV - Work Plan / Goals to be achieved: Assessment of reliability in emotion recognition, based on machine learning methods and using EEG signals. The aim is to induce
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; Jorge Manuel Oliveira Henriques IV - Work Plan / Goals to be achieved: Assessment of reliability in emotion recognition, based on machine learning methods and using EEG signals: The aim is to induce
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methods for the prognosis of diseases related to climatic factors, based on machine learning models and using hospitalisation data from municipalities in Brazil. Plan: - Study of the database
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Computer Engineering, enrolled in a non-degree-granting course. Preferred requirements: Knowledge of programming, computational estimation techniques, computational learning, deep learning and real-time
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learning models, taking into account domain-specific information. One of the key expected outcomes is the ability to provide structured information to improve machine learning models, including: identifying
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development of classical feature engineering and machine learning approaches for the segmentation and classification of respiratory sounds and lung EIT images 2. Research and development of deep learning
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and criteria: - Criterion 1: Graduation average – 50%; - Criterion 2: Academic performance in subjects related to Machine Learning and Artificial Intelligence – 50%; VII.II- I – In the evaluation
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. The candidate should also have knowledge of methods for analyzing large amounts of data, which should also be processed using machine learning techniques for the development of predictive models. The candidate
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and development of the designed systems. They should also have knowledge of methods for analyzing large amounts of data, which should also be processed by machine learning to develop predictive models
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- Legal admission requirements I.I - Grant Recipients: The scholarship is intended for Masters in Computer Engineering, enrolled in a PhD programme in Computer Engineering, Data Science Engineering, or