29 evolution "https:" "https:" "https:" "https:" "https:" "https:" scholarships at Universidade de Coimbra in Portugal
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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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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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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 . Only applicants who have completed the cycle of studies leading to a Bachelor’s or
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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
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: University of Coimbra III- Scientific supervision/coordination of the grant: Luís Fernando Morgado Pereira de Almeida IV - Work Plan / Goals to be achieved: The work plan includes the development of activities
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that combine machine learning and classical methods. Work Plan: -State-of art revier and publication of a review paper -Development of classical approaches -Development of hybrid approaches -Journal publication
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MANET and performing adaptive data sampling in aquatic use cases within the REMORA project. 2. Development of a decentralized, self-organizing data aggregation method for swarm state estimation. 3. Design