22 algorithm-development-"Multiple"-"Prof"-"Prof" Fellowship positions at Universidade de Coimbra
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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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Assignment The University of Coimbra opens a call for the assignment of a research grant, with one position(s), under the project PS1521, title Development of pathophysiological models. The call is governed by
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development of a research project in Organic Chemistry, leading to the Doctorate in Chemistry. The research project will focus on organic synthesis and mechanistic studies in fundamental Organic Chemistry. The
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, Computer Engineering; Knowledge of C/C++ programming, etc., and of software development and integration will be valued; fluency in English (spoken and written); prior knowledge of Computer Vision, Computer
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, and Conviviality, with the following main objectives and activities. Objectives - Contribute to the development and assessment of the Family Food Heritage solution within CONVIVIUM. - Advance research
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the laboratory work necessary to identify species, process biological samples, and conduct statistical analyses and processing of the data obtained; e) prepare a scientific article on the topic, contributing
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funded by Fundação para a Ciência e a Tecnologia (FCT), I.P., through national funds and the European Regional Development Fund (ERDF) through the Thematic Programme for Innovation and Digital Transition
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-augmented Secure Software Development. 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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Regional Development Fund (ERDF) through the Thematic Programme Innovation and Digital Transition (COMPETE 2030), Portugal 2030, and the European Union | Operation no. 15895, operation code in the Funds
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- Work Plan / Goals to be achieved: The post holder will join the DETECT project, which aims to develop an artificial intelligence-based tool to identify individuals at clinical high risk for psychosis