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) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Applying anomaly detection algorithms for streaming network data. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND
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testing. The work is expected to strengthen the reliability and predictive accuracy of SGB and related machine learning methods, i.e., those that share common algorithmic steps, in contaminated settings. 4
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optimizations, such as new data caching algorithms. Develop a prototype that integrates the optimizations and experimentally evaluate the prototype.; Integrate the optimizations with a new modular and flexible I
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; - collaborate in the preparation of technical reports on the algorithms, mechanisms, models, or protocols developed; - develop new modules to enable the simulation and/or experimentation of emerging wireless
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AND TRAINING: - survey and analyze the state of the art in emerging wireless networks, including simulation aspects; - collaborate in the preparation of technical reports on the algorithms, mechanisms
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waveguide setups and development of PCBs for reconfigurable intelligent surfaces (RIS).; 2. Implementation, testing, and optimization of RIS control algorithms on microcontroller-based platforms.; 3
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of a multi-modal dataset.; - Implementation of a software module for storing datasets according to a pre-defined standard.; - Development of routines for testing existing ML algorithms on a multimodal
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sufficiently “compact” (i.e. algorithmically small and computationally efficient) to enable incorporation in integrated PED models. The development of these compact models will involve collaboration with several
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Europe | about 2 months ago
manufacturing, development of machine learning algorithms and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen
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application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial peptides Perform and support experimental studies across the METAMIC project