133 algorithm-development-"Multiple"-"Prof"-"Prof"-"St"-"Simons-Foundation" positions at Universidade de Coimbra
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, emphasising the integration and analysis of multiple clinical datasets, including diagnoses, pathology, and genomic data. Using cutting-edge data science and machine learning techniques, the goal is to develop
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activities will be developed in the Power Electronics area, focusing on programming control algorithms on a Xilinx FPGA. This project aims to implement internal fault tolerance in a power electronics
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the execution of the following tasks related to modelling the incineration process of the pilot units, with the following main objectives: - development of evolving algorithms based on Machine Learning
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of Article 4 of Decree-Law No. 74/2006, in its current wording, provided that, under subparagraph e) of Article 3 of RBI-FCT, they are developed in association or cooperation between the higher education
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referred to in subparagraph e) of paragraph 3 of Article 4 of Decree-Law No. 74/2006, in its current wording, provided that, under subparagraph e) of Article 3 of RBI-FCT, they are developed in association
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, usability, and integration into well-being programs; - capacity of planning, developing, and implementing health and well-being interventions, while effectively managing multiple tasks and maintaining a high
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individual synapses to whole neurons, there are multiple physical barriers constraining electrochemical diffusivity and introducing selectivity and competition in the adaptive processes. Their existence and
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of Article 4 of Decree-Law No. 74/2006, in its current wording, provided that, under subparagraph e) of Article 3 of RBI-FCT, they are developed in association or cooperation between the higher education
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Development of pathophysiological models The call is governed by this Notice of Opening, the University of Coimbra Research Grant Regulations (RBI-UC), subsidiarily by the Research Grant Regulations
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for developing machine learning models for the automatic identification of species from images collected through electronic monitoring systems (Work Package 3 – Bycatch Monitoring). The candidate will be involved