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validate the tools identified and/or developed, using as a reference case the remote training of grid operators in operational scenarios for power networks with a high penetration of renewable energy—one
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-time computational simulation in operating scenarios for power networks with a high penetration of renewable energy—one of the services to be offered by the collaborative laboratory currently under
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integration and thermal networks; • proficiency in Python; Minimum requirements: - knowledge in programming; - fluency in English and Portuguese (written and spoken). 5. EVALUATION OF APPLICATIONS AND
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PRESENTATION OF THE WORK PROGRAMME AND TRAINING: • Collaboration in the design and prototyping of a radar + video system for motorcycles.; • Development of software modules for automated data collection
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - experience in em Agile, DevOps, Arquitectura de Software e Cloud Computing. Minimum
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of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - Experience with software installation and configuration
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The awarding of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - Experience in software testing implementation
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: Experience in developing optimization problems and experience with GAMS software; Fluency in Portuguese (spoken and written) ; Minimum requirements: Proven experience in R&D work on electricity and renewable
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neural networks, enabling us to estimate the reliability of a single decision of this algorithm. Regarding generalisation, recent self-supervised learning paradigms have strong synergies with the multi
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. Functional testing of developed PCBs, including experimental validation of electronic circuits and S-parameter characterization using a vector network analyzer (VNA).; 4. Experimental characterization