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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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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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Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab | Portugal | 21 days 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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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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from academic degree recognition processes. Preferential factors: a. Knowledge of developing artificial intelligence/machine learning (AI/ML) models and classifiers suited for embedded systems
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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
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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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Area: Computer Science 2. Admission Requirements: Graduates (Licenciatura) in computer engineering or related area, with experience in Machine Learning/Deep Learning methods/techniques. 3. Project
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possible renewals, an accumulated period of 3 (three) years in this type of scholarship, consecutive or interpolated. Proven knowledge in: Data Science (Python) Machine Learning (Python) Remote Sensing
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experience in Data Science/Machine Learning projects or initiatives (professional projects, coursework, internships, personal projects or hackathons, etc.) Knowledge and experience with the use of tools