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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
will develop computer vision, machine learning and control algorithms for a robot to perform packaging tasks. Human demonstrations will be used to generate data for learning. These data will encompass
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-of-the-art models for computer vision based on Machine Learning. Work plan: - Analysis and study of existing resources. - Analysis of the state of the art in universal adversarial attacks on computer vision
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-of-the-art models for computer vision based on Machine Learning. - Analysis and Study of existing resources; - Analysis of the state of the art in adversarial attacks and adversarial training and their
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the following conditions: OBJECTIVES | FUNCTIONS The purpose is to continue the research on Machine Learning methods applied to optimization techniques, in particular for the veicule routing problem. The idea is
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objectives: 1 – Development of a tool for identifying operating regimes using machine learning techniques. 2 – Development of a tool for identifying the causes of process eco-efficiency degradation using
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, Economics, Management, or related fields. [1] ; Be a student enrolled in a doctoral program in Computer Engineering or Computer Science - a requirement to be duly proven at the time of hiring. 2; 3. Preferred
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NIMSB Technology Platform Leaders:Data Science, Single-Cell & Spatial Omics, Proteomics/Metabolomics
, machine learning–based computational approaches, and the development and application of human-derived microphysiological models, including organoids and organ-on-a-chip systems, to enable earlier disease
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compression, event-based or neuromorphic vision, signal processing, machine learning or deep learning for visual data. - Motivation for research and scientific dissemination. - Good communication skills in
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- The curriculum evaluation considers the candidates' academic and professional achievements based on the following weights and criteria: - Criterion 1 - Academic performance in subjects within the areas of Machine
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“Enhancing Machine Learning Approaches for Spatially Dependent Data in Fisheries and Environmental Research” (CMAT, University of Minho), reference 2024.15617.PEX, financed by national funds through