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Plan / Goals to be achieved: The objective of this grant is to develop the fundamental steps for training and evaluating predictive models for code comprehension using multimodal data, namely EEG, HRV
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an opinion issued by the respective supervisor(s). The report models, performance evaluation criteria, and the grant contract model are those approved under the University of Coimbra's Research Grant
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for developing machine learning models for the automatic identification of species from images collected through electronic monitoring systems (Work Package 3 – Bycatch Monitoring). The candidate will be involved
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stipulated in Article 7 of the RBI-UC, subject to an opinion issued by the respective supervisor(s). The report models, performance evaluation criteria, and the grant contract model are those approved under
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Development of pathophysiological models The call is governed by this Notice of Opening, the University of Coimbra Research Grant Regulations (RBI-UC), subsidiarily by the Research Grant Regulations
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the end of the grant contract, as stipulated in Article 7 of the RBI-UC, subject to an opinion issued by the respective supervisor(s). The report models, performance evaluation criteria, and the grant
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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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models parameters, aiming to uncover possible predictors of upcoming seizures. The initial focus will be on classic approaches, such as Kalman Filters, followed by the consideration of hybrid approaches
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supervisor(s). The report models, performance evaluation criteria, and the grant contract model are those approved under the University of Coimbra's Research Grant Regulations. Where to apply Website https
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and knowledge transfer T2- Selection and fine tuning of large language models for automatic classification of reports T3- Experimental evaluation. V - Initial grant duration: 5 months (as long as it