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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - knowledge of wireless networks; - knowledge of Artificial Intelligence models.; Minimum
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.; - Develop skills in artificial intelligence and machine learning techniques for analyzing operational data and detecting anomalies, using foundational model approaches (e.g., GridFM project, LF Energy
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learning models for generating artificial data using generative models. The result will be high-fidelity medical data. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge
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programme of R&D projects geared towards the development and implementation of advanced cybersecurity, artificial intelligence and data science systems in public administration, as well as a scientific
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intelligent surfaces ; - Identification and selection of the most adequate optimization methods to address the proposed workplan: ; - Develop the research skills through the application of the selected methods
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TEC. 2. OBJECTIVES: - broaden knowledge of the state of the art in the scientific field of DevOps Cloud Architectures, Infrastructure as Code (IaC) and on-demand, intelligent configuration of self