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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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, with applications ranging from scientific research to medical imaging and marketing analysis. With the ever increasing amount of learning data, these algorithms face computational challenges
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Development Fund (FEDER), through the National Innovation Agency (ANI), the Framework Programme Portugal 2030 – Programa Inovação e Transição Digital | COMPETE 2030, medida eixo SIID – Internacionalização de I
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of Mechanical Engineering, University of Minho; e) Substitute Member: Dr. Sara Cristina Soares Madeira, Entry-level PhD researcher at the Centre for MicroElectroMechanical Systems (CMEMS-UMinho), University
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learning-assisted computational pipeline for the automated detection of point defects in atomic-resolution scanning transmission electron microscopy (STEM) images. Using monolayer MoS₂ as a model system, the
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Sistema Avançado melhoria do desempenho da qualidade do ar interior aplicado aos sistemas de AVAC para as unidades e infraestruturas de saúde, (AT AirHealth2024), financed by national funds through Agência
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participate in the bioinformatic analysis of host and pathogen genomic data, primarily focusing on evolutionary, population genetics, and phylogenetic analyses; e) Present and disseminate the project's results
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) Substitute Member: Dr. Vanessa Fernandes Cardoso, Assistant Researcher at the Centre for MicroElectroMechanical Systems (CMEMS-UMinho), University of Minho; e) Substitute Member: Doctor Nuno Miguel Magalhães
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artificial exosomes for nose-to-brain delivery/Centre of Molecular and Environmental Biology, (2024.17197.PEX), financed by national funds through Fundação para a Ciência e a Tecnologia, under the following