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Field
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(AutoML) platform to output Machine Learning/Deep Larning models focused on image analysis. In this sense, the focus will be the development of several modules: a module to load, process and store images
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Learning and Computer Vision Objetives: This work aims to study, develop and implement computer vision methods to detect and classify areas with imaging alterations from MRI and CT scans
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: Research Field: Machine Learning/Pattern Recognition Objectives: AI-based module for energy consumption and quality control optimization. Work plan: The planned work involves collaboration in the process of
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: Research Field: Machine Learning/Pattern Recognition Objectives: AI-based module for energy consumption and quality control optimization. Work plan: The planned work involves collaboration in the process of
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; Programming skills in Python and C++; Basic knowledge of Artificial Intelligence techniques as Machine Learning e Computer Vision; Knowledge of Deep Learning (i.e., Pytorch, Tensorflow, JAX) and Computer Vision
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the following profile: Enrolled in a master’s degree in computer engineering or related fields; Knowledge of Extended Reality application development and/or knowledge of machine learning, information
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the port area; Good technical and scientific knowledge in mobile development, and/or web programming, and/or human-computer interaction (UX), and/or application of machine learning; Sense of responsibility
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Applications — Award of a Research Initiation Grant (BII) Call Reference: BII_1_DEEC A call is hereby opened for the award of one (1) Research Initiation Grant (BII) under the scope of the Learning Environments
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) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Development of novel Machine Learning techniques applied in systems/networks research, which includes, but is not
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Pose EstimationStrong background in computer vision and machine learning applied to pose estimation and visual servoing; Experience with OpenCV, PCL (Point Cloud Library), PyTorch/TensorFlow, and 3D