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an emphasis on the development of methodologies and techniques for Evolutionary Computation and Machine Learning. Work plan: Review of the state of the art in Machine Learning and Deep Reinforcement Learning
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to secretaria.mia@uc.pt . Reference of the expression of interest: MIA-AR-2025-03 Scientific area: Data Science and Machine Learning Work plan/objectives: The “Continuous Learning Lab”, led by Dr José Sousa
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for developing machine learning models for the automatic identification of species from images collected through electronic monitoring systems (Work Package 3 – Bycatch Monitoring). The candidate will be involved
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the output of a machine learning model, capable of assessing the reliability of a given input/output. 2. State of the art regarding non-invasive blood pressure estimation, focusing on the use
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Machine Learning. Work plan: Review of the state of the art on Evolutionary Algorithms and image tampering detection; Implementation of an evolutionary algorithm for image tampering detection
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, and eye tracker data. Work Plan: - Multimodal feature extraction from EEG, HRV, gaze dynamics, and pupil size data; - Signal fusion and model training using interpretable machine learning models (e.g
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(spoken and written), academic excellence, autonomy, curiosity, and attention to detail. Resumes demonstrating knowledge of programming in Python and/or Matlab; computer vision, image processing, learning
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with machine learning. Evaluation of the final solution. V - Initial grant duration: 5 months V.I - Renewal Possibility: Possibily renewable VI - Funding and financial conditions of the grant VI.I
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(spoken and written), academic excellence, autonomy, curiosity, and attention to detail. Resumes demonstrating knowledge of programming in Python and/or Matlab; computer vision, image processing, learning
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that combine machine learning and classical methods. Work Plan: -State-of art revier and publication of a review paper -Development of classical approaches -Development of hybrid approaches -Journal publication