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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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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 4 days ago
research in microbial genomics, in particular related to natural products biosynthesis and using metagenomics and genomics datasets. Experience in machine learning and the application of artificial
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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
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manufacturing, health and transportion: Interperability of systems Data Management Big data analytics AI and Machine Learning Experience in the organization of international events such as workshops and
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Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab | Portugal | about 1 month ago
Python Machine Learning Libraries (PyTorch, Keras, etc.); statistical and machine Learning expertise and supervised and unsupervised methodologies; Valuable Bonus Skills include: experience with Unity3D
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Engineering/ Electrical Engineering. 2. Admission Requirements: Bachelor's degree in Computer Engineering, Systems and Information Technologies Engineering, Electrical and Computer Science Engineering, or in a
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methodologies, including the manipulation and processing of satellite imagery and data from equivalent remote-sensing platforms (e.g., UAVs), as well as the development of machine-learning approaches to enhance
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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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. Project Title: Machine learning techniques for crosstalk mitigation and new passive optical network architecturesHost institution: Iscte-IUL, PortugalThe LUMIRing project aims to deploy a MCF test bed
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large sample size; d. Experience in integration of multi-omics using machine learning approaches; e. Experience in participation of research teams or projects. Candidates must be enrolled in a doctorate