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models; Participation in the implementation and execution of laboratory tests for validation of the platform's algorithms, interfaces, and subsystems; Support in the analysis of experimental results and in
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analysis, performance evaluation, and liaison with local and industrial partners. Contribution to the development of digital tools, models, and algorithms related to the simulation, optimisation, and
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of Coimbra III- Scientific supervision/coordination of the grant: Rui Paulo Pinto da Rocha IV - Work Plan / Goals to be achieved: 1. Development of algorithms for swarm robotics and human–swarm interaction 2
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the thermomechanical performance of the refractory masonry; Application of advanced statistical analysis algorithms, including sensitivity analyses and comparisons of different algorithm types; Development
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literacy algorithm to be integrated into an API for health platforms, as well as contributing to the design and testing of the virtual library and associated educational materials. The grant holder will also
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period of 12 months, possibly renewable up to a maximum of 36 months, scheduled to start on March 2026. 2. WORK PLAN AND WORKPLACE: The project will investigate the developed algorithms and methods
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requirements: Experience using deep-learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating on scientific projects. Publications on deep-learning topics. 4. Work Plan
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be duly proven at the time of hiring. 2; 3. Preferred requirements: Experience using Machine Learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating
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an international call to hire 1 (one) Researcher, in form of an Unfixed-Term Contract and at full-time under the Research Project “SmartADC Design of a ultra high-speed time-interleaved ADC using genetic algorithms
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-inspired selection). 3-Investigate the integration of QIEC with Quality-Diversity (QD) algorithms such as MAP-Elites.(month 2-3) 4-Explore the use of Evolutionary Computation to generate and optimize quantum