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developed: Write and maintain code to implement the core functionality and system logic that powers the application. Design algorithms and procedures for negotiating agreements between transport companies
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for the acquisition and storage of radiofrequency data. Develop (train and validate) AI and ML algorithms to detect and mitigate RFIs. Implement other RFI detection and mitigation algorithms (pulse blanking
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, and WINC projects, focusing on quantum error correction, quantum machine learning algorithms, and other related topics, as well as contribute to research efforts in other CBA-N3Cat group projects
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. Furthermore, he/she will participate in the development of computer vision algorithms for hyperspectral image analysis and mathematical models for knowledge inference, with the aim of estimating the key
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on USRPs to test AI-based communication algorithms under realistic channel conditions. The offered position is an excellent opportunity to further develop the candidate’s SDR skills, acquire state-of-the-art
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. Specifically, its activities will be developed in the following areas: - Design and creation of technical content and audiovisual material about IA algorithm, machine learning techniques and IoT. - Support to
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algorithms using artificial intelligence for the implementation of cognitive autonomous robots. Where to apply E-mail ricardo.sanz@upm.es Requirements Research FieldEngineering » Industrial
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. Development and experimental validation of control algorithms in a laboratory environment. Communicate and disseminate research results through high-quality scientific channels including high impact scientific
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sequences, networks, trajectories, images, etc. - Design, programming, optimization, and parallelization of machine learning algorithms. - Search in repositories and bioinformatics of DNA sequences
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algorithms to develop intelligent resource detection models. This position is funded under the HUNOSA-25-2 project and offers a unique opportunity to contribute to cutting-edge research in planetary science