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/2022 ”, funded by the Fundação para a Ciência e a Tecnologia, I.P. through national funds under the ERA-NET Cofund JPcofuND-2, under the following conditions: Scientific Area: Non-invasive Neuronal
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and evaluation of a new protocol for Dynamic Multi-Party Computation as a Service for asynchronous networks. Legislation framework: Research Fellowship Holder Statute, in accordance with Law 40/2004
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requirements: Presentation of the academic qualifications and/or diplomas, if applicable. Enrolment in a PhD in Computer Science or related area. Work plan: The goal is to investigate and develop IoT network
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system components. Define target values for the façade’s U-value for different use cases. Legislation framework: Research Fellowship Holder Statute, in accordance with Law 40/2004, of 18 August, in its
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diplomas, if applicable. Enrolment in master. Work plan: This project aims to develop an artificial intelligence model with convolutional neural networks (CNN) trained on orthorectified aerial imagery and
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: Aligning climate action with long-term climate and development goals”, “SDSNASSOCIATION_SG_PR04109”, financed by UN Sustainable Development Solutions Network (SDSN Association, Inc.), under the following
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Learning (CNN, RCNN), Large-Scale Language Models (e.g., transformer-based models such as Llama), and Statistical Network Models. The work also includes the writing of technical reports and scientific
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Engineering, skills in the areas of Geographic Information Systems, Geodesy and Hydrography. Additional optional skills and qualifications: Experience with GIS software and geospatial analysis tools. Experience
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database management and analysis, including the use of statistical software (namely R, SPSS, STATA, or Python) and, preferably, geospatial analysis tools (QGIS, ArcGIS, or equivalents); Knowledge in applied