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of machine learning and deep learning methods and classification of health and wellness parameters. Data acquisition, as well as the preparation of presentations, scientific publications, and technical reports
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factors: Prior experience in developing algorithms for biomedical image processing (especially aligned with the research group's areas) and machine learning/deep learning techniques. Prior knowledge of data
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machine-learning methods for sample segmentation and classification. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The fellow will join the INESC TEC team within the LIBScan project, carrying
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Analysis and Decision Support - Applying statistical and machine learning methods to interpret the data, identify trends for optimizing aquaculture conditions.; • Experimental Validation - Conducting