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) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: The successful candidate will develop signal and image processing techniques, as well as apply machine learning
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with researchers, master’s students, doctoral candidates, and postdoctoral fellows working on diverse topics such as Natural Language Processing, Information Retrieval, Machine Learning, and Information
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: Experience in research projects, and writing of scientific papers. Minimum requirements: Experience in Computer Vision and machine learning. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection
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new approach based on physically inspired hybrid machine learning models for generating artificial data using generative models. The result will be high-fidelity medical data. 3. BRIEF PRESENTATION
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, Machine Learning, and Information Extraction. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Collect data and build the annotated dataset, in collaboration with the computational linguistics team
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Retrieval, Machine Learning, and Information Extraction. The ideal candidate should be enthusiastic about contributing occasionally to other related projects and eager to thrive in a collaborative and
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TRAINING: - extend the knowledge of the state of the art in computer vision and machine learning for cancer characterization; - identify and select the appropriate methods for the study in question
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. Preference factors: Experience in research projects. Minimum requirements: Experience in Computer Vision and machine learning. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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. The programme will involve implementing simulation models that incorporate centralized protection approaches, combined with optimization tools and machine learning techniques to enhance protection performance