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modelling of nature-based solution to enhance the resilience of Mediterranean agro-silvo-pastoral ecosystems and landscapes, with reference GA nº101156076, taking place at the Forest Research Centre (CEF) of
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for a research grant within the framework of project 2023.11234.PEX – GAI4FD - Evaluation methodology for Generative Artificial Intelligence Super-Resolution models for Fluid Dynamics, with DOI https
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, financed by Fundação para a Ciência e a Tecnologia, I.P ) through national funds, within the scope of the Water4All European partnership, , under the following conditions: Scientific Area: Chemical
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extracellular vesicles using in vitro and ex vivo models. V - Initial grant duration: 6 months V.I - Renewal Possibility: Possibily renewable VI - Funding and financial conditions of the grant VI.I - Monthly
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) to develop research towards the increased use of non-wood forest products from the Portuguese forests, in accordance with the following conditions: 1. TYPE, DURATION OF THE SCHOLARSHIPS and EXPECTED BEGINNING
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metrics for determining the output of a machine learning model, capable of assessing the reliability of a given input/output. 2. State of the art regarding non-invasive blood pressure estimation, focusing
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), Northern Regional Program (Norte 2030) of Portugal 2030.", under the following conditions: 1. Scientific Area: Engineering 2. Admission requirements: i) Student enrolled in a PhD in Intelligent Systems
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Management & Landscape Architecture of Research Unit LEAF, of the Instituto Superior de Agronomia, financed by Fundação para a Ciência e a Tecnologia (FCT), MIT-Portugal), under the following conditions: 1
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ambient air. V - Initial grant duration: 3 months (not being able to go beyond the end of the project) V.I - Renewal Possibility: Possibily renewable VI - Funding and financial conditions of the grant VI.I
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beyond the end of the project) V.I - Renewal Possibility: Possibily renewable VI - Funding and financial conditions of the grant VI.I - Monthly grant amount (paid by bank transfer at the end of each month