40 evolution "https:" "https:" "https:" "https:" "https:" "University of St" scholarships at Universidade de Coimbra
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for the piloting, demonstration and scale-up of innovative seaweed/algae-based solutions and ecosystem building. Where to apply Website https://apply.uc.pt/ Requirements Research FieldBiological sciences
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of the state of the art in Human-in-the-Loop solutions in federated environments. 2) Development of a proposal with customized requirements for physical-emotional variables and ethical principles. 3) Development
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Maria Rocha Durães IV - Work Plan / Goals to be achieved: Perform bibliographic research, laboratory development, results processing and reporting, and participate in the dissemination of results within
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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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an emphasis on the development of methodologies and techniques for Evolutionary Computation and Machine Learning. Work plan: Review of the state of the art in Machine Learning and Deep Reinforcement Learning
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. VI.IV - Funding: The grant(s) assigned under this call will be funded by Foundation for Science and Technology through national funds and by the European Regional Development Fund (ERDF) through
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) assigned under this call will be funded by Fundação para a Ciência e a Tecnologia (FCT), I.P. and the European Regional Development Fund (ERDF) through the Thematic Programme for Innovation and Digital
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achieved: The research will address the challenges of energy efficiency, demand-side management, and sustainable urban development through advanced modelling and optimisation approaches. It will also explore
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of automatic recognition). Candidates should consult the DGES portal for more information at https://www.dges.gov.pt/en . All requests for automatic or level recognition made to the University of Coimbra (UC
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subsequent treatment. Work plan: Development of the decision support system for oncological care. Building the knowledge base, based on rules derived from existing practices. Complementing the recommendations