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this short-term project we shall use active learning to accelerate the training of deep learning algorithms for optimising 2D material van der Waals (vdW) structure discovery. The goal is to make model
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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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analysis, AI algorithm modeling, testing, and integration into functional systems within the project scope. Specifically, in activities related to behavior modeling from IoT device data, generative AI
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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
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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