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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 1 month ago
project is develop computational models for the high-fidelity finite element (FE) analysis of the behaviour of advanced thermoplastic-based composite materials. These models will effectively link
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validation of the solutions being created. Activities will include the selection and integration of sensors and data acquisition systems, the implementation of algorithms for data compression and analysis, and
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biological signal analysis and classification pipeline for differentiation between different class types. Assembly of a data acquisition bench. Documentation of all work performed and the use of the bench
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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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customization process by conducting laboratory tests. - Improvement of the data workflow for real-time processing and sharing. - Data collection in experimental and real-world environments - Data analysis and
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in applied optimization • Knowledge of digital twins • Experience in data analysis and visualization. Minimum requirements: • Experience in Python; • Knowledge of optimization algorithms; • Knowledge
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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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infrastructures for controlled, secure, and private data sharing ; - Analysis of technologies for implementing a data space in an industrial context within ocean technologies ; - Design, development, and
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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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research skills in the area of wireless energy transfer applicable to agricultural robotics.; • Develop critical and methodological skills in the review and analysis of the state of the art of inductive