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Objectives: - Completion of the characterization of nanomateriais on in vivo models of vaccination - Completion of the characterization of nanomateriais on in vitro and in vivo cancer models - Analysis
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, whether consecutive or not. 13.Fellowship Agreement model: After the candidate selection and all information is received, it will be signed a fellowship agreement in accordance with the model here 14
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this type of fellowship, whether consecutive or not. 13.Fellowship Agreement model: After the candidate selection and all information is received, it will be signed a fellowship agreement in accordance with
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: Development and calibration of numerical models of pilot networks to explore the use of multiple monitored parameters (pressure, flow rate, basic and advanced water quality parameters) for anomaly detection
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, for the project “PREDICT-OAE project (From data to PREDICTion: modelling temporal ecological–biogeochemical links under Ocean Alkalinity Enhancement”, financed by internal funds from CIÊNCIAS and FCiências.ID
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Objective: The objective is to understand the relationship between neuronal responses and the space of generative possibilities of the model, navigating regions that are not typically reached by conventional
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tools. Processing of collected data; Implementation of Machine Learning; Development/implementation of the model prototype in the digital solution (app/platform) to support the clinical trial
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Life and Health Sciences Research Institute (ICVS), from the School of Medicine (EM) of the University of Minho | Portugal | 9 days ago
“Application deadline and submission” of this Call, the candidates must submit in the application process a Declaration of Honor regarding the benefited Research Fellowships, issued as defined in the model
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databases and genome-scale metabolic models. Additionally, this fellow will develop robust error-checking and validation mechanisms to minimise misinterpretations. Applicable legislation and regulations
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. Improve the SNN-based model head and compare its performance and efficiency with the standard (non-spiking) model. 3. Add simple explainability methods and check how the models behave under fairness and