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assigned in each evaluation criterion, and considering the weighting factor given to each parameter. In this process abstentions are not allowed. In the event of a tie among candidates with the same highest
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characterization techniques, requiring visualizing, analysis and interpretation of experimental data. The research results shall be published in peer-reviewed scientific journals and presented at conferences
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: • To understand the challenges associated with the collection, quality and analysis of longitudinal health data; • To develop skills in the design, implementation and evaluation of data science-driven approaches
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of astronomical techniques (such as observing, data reduction and analysis, instrumentation and software development, modelling and simulations) involving instrumentation for or astronomical datasets from ground
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the scholarship will enable the scholarship holder to gain experience in the development of marine robotic systems, hardware integration, the preparation of experimental trials, data analysis, and the production
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PRESENTATION OF THE WORK PROGRAMME AND TRAINING: • Review the state of the art on transparent metasurfaces, Reconfigurable Intelligent Surfaces (RIS), and transparent conductive technologies based on metal-mesh
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: - Any other elements the candidate considers relevant. - Motivation Letter. - Bachelor's degree academic transcript. VIII.III - All application documents must be submitted in Portuguese and/or English
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well as the analysis of communication and processing requirements associated with the systems in question. The work will also involve processing and integrating data from hydrophones, DAS systems, and external
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modelling, analysis of industrial cases, stakeholder engagement, and iterative validation of the artefacts produced, contributing to the responsible and human-centred integration of Artificial Intelligence in
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
including near-future laser scenarios and edge cases. Perform sensitivity analysis and quantify uncertainties/error bars for model predictions. Finalize key figures for results. Month 6 — Finalization