26 evolution "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" Fellowship positions at Universidade de Coimbra in Portugal
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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 this Notice
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Development Fund (ERDF) through the Innovation and Digital Transition Program (COMPETE 2030) of Portugal 2030| reference of operation no. 17378, operation COMPETE2030-FEDER-01187700 on Balcão dos Fundos.[LM4.1
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of Coimbra III- Scientific supervision/coordination of the grant: Bernardete Martins Ribeiro; PJorge Manuel Oliveira Henriques IV - Work Plan / Goals to be achieved: This project proposes the development
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Engineering, Faculty of Science and Technology, University of Coimbra III- Scientific supervision/coordination of the grant: Paulo Jorge Carvalho Menezes IV - Work Plan / Goals to be achieved: Development
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method applied; b) Based on the score of their academic qualifications. VII.VIII - All provisional and final jury decisions must be justified, recorded in minutes, and published on https://apply.uc.pt
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Strategies for Sustainable Invasive Plant Management, Ecosystem Restoration, and Community Engagement) project and involves the collaboration of the fellow in the implementation and development
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qualifications. VII.VIII - All provisional and final jury decisions must be justified, recorded in minutes, and published on https://apply.uc.pt/ . VII.IX - Jury Composition: President: Fernando Jorge Penousal
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of the grant: André Manuel dos Santos Mendes IV - Work Plan / Goals to be achieved: Research and project activities will be carried out in the field of Power Electronics, focusing on the development
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Development Fund (ERDF) through the Regional Programme (CENTRO 2030) of Portugal 2030; reference of operation 14443, operation code CENTRO2030-FEDER-00585600 on Balcão dos Fundos. [LM5.1] VI.IV - Information
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in several tasks within the project’s work plan, including: - Development of deep learning models (e.g., convolutional neural networks and vision transformers); - Presentation of results at consortium