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, advanced studies, specialized training). Preferential factors: Professional or academic experience in Machine Learning; Professional or academic experience in Finite Element Modelling; English language
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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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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
. The work will include the analysis of radiation levels using realistic laboratory interaction models (interaction chamber, walls and laboratory dimensions), taking into account the spectrum and divergence
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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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periods. b) Relevant experience in the development of drug delivery systems. c) Experience in the design and application of in vitro models for pulmonary and systemic administration. d) Training and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
method an option of the Fellow by Wire Transfer/Check. Eligibility criteria Admission Requirements: a) hold a master’s degree in Biomedical Engineering, or related areas; b) be enrolled at the date
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improved well-being, specifically in the areas of sleep, stress, and intestinal inflammation. The activities include screening bioactive peptides in cellular models of the gastrointestinal tract to identify
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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
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of the project “PROSPER: Predictive models for sustainable protein recovery”, funded by FEDER and by National Funds through FCT (Operation No. 15391 — COMPETE2030-FEDER-00907300), under the following conditions