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Field
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the context of climate change and the green transition. Expected duration of project execution: 36 months, September 2025 – August 2028. b. Scientific field: Sociology c. Work plan, tasks: The selected
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on absolute merit will submit themselves, aimed at clarifying aspects related to the curriculum and the scientific-pedagogical plan, taking into account the general functions assigned to university teachers by
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, including an email address expressly designated for receiving notifications within the scope of the electoral procedure; ii. Detailed curriculum vitae of the candidate, dated and signed; iii. Document proving
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-01458500, Project No. 17803), funded by FEDER through the Innovation and Digital Transition Thematic Program, under the terms of Call No. COMPETE2030-2024-6. This project, which will run until the 31st
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of Decree-Law nr 66/2018, of 18th August, and all formalities established there must be fulfilled by applications deadline. 2. Work plan The work plan for this call is as follows: • Reception and processing
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biology, within the scope of the ClimAGRO4.0 Project, ref. M2030-FEDER-03050600, Technological Innovation in Monitoring, Production, Sustainability and Climate Adaptation of Agri-food Systems, under
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the Scientific-Pedagogical Project dimension (PCP) – 10 % Strategic plan relating to the lines of research, teaching and university extension in the area of Chemical Engineering that the candidate proposes
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-Hong Kong-Macao Greater Bay Area (GBA). The GBA is rapidly developing into one of the leading technology and innovation hubs of the world. UM is placed No. 145 in the THE World University Rankings and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 25 days ago
of an application form, made available at https://ist-id.pt/recursos-humanos/investigadores/ electronic address, addressed to the President of Instituto Superior Técnico Association for Research and Development (IST
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the PORTUGAL2030 Programme, under the following conditions: Work Plan and Objectives to Reach: The work to be carried out aims at the research and development of Computer Vision and Machine/Deep Learning algorithms