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. OBJECTIVES: - To expand knowledge of the state of the art in the area of antenna characterization systems; - Identification and selection of the most adequate optimization methods to address the proposed
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evaluation of the Exclusion Zone around an Active Antenna in urban mobile communications scenarios, accounting for the mobility of users, the diversity of the provided services and the environment
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of the art in the area of electronic devices for antenna applications ; - Identification and selection of the most adequate optimization methods to address the proposed workplan: ; - Develop the research
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and optimisation algorithms, focusing on their practical application in the context of the RaceEngineerAI project. Tasks include: - Developing models capable of simulating the behaviour of racing
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Platforms. Scientific Area: Wireless Technologies Group: Antennas and Propagation – Lx Work Objectives: This research project will investigate classical and quantum light phenomena in non-Hermitian systems
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 19 days ago
for Science and Technology, I.P., both in their current wording. 2. Activity objective: Research and implementation of advanced Optimization and decision-support algorithms using Artificial Intelligence applied
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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based on GRAND) and multi-antenna wireless communications; - Should also have relevant experience in implementing these physical layer techniques in MATLAB. Additional Information Benefits Monthly salary
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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions