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two years followed or interpolated, in this type of scholarship; Requirements: Clear demonstration of skills in modeling and simulation of solids, fluids, and their interaction; clear demonstration
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chemistry (e.g., reaction kinetics, enzymes, titrations, mixing and dilutions); Physical modelling (e.g., COMSOL). Personal Skills “Hands-on” approach together with a high commitment in respecting working
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mapping and imaging experiments to probe local heat transport and phonon dynamics; Perform finite element modeling (FEM) (e.g., using COMSOL Multiphysics) to simulate thermal transport processes and support
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; Knowledge of stable isotope techniques and methodologies - information provided in the CV and/or in the motivation letter; Experience in data analysis and ecological modelling (GLM, GLMM and the like
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of the Large-Scale Language Model of the Portuguese Language of Portugal (Automatic Multimodal Language Assistant with Artificial Intelligence), reference AMALIA, inserted in measure RE-C05-i08 of the Recovery
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generative models for the creation of human movement datasets for training AI models; - Prepare activity reports and scientific articles. 4. REQUIRED PROFILE: Admission requirements: - Master's student, with a
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learning models for generating artificial data using generative models. The result will be high-fidelity medical data. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge
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protocols for data collection with motion capture systems and curation of the resulting data - Design generative models for the creation of human movement datasets for training AI models - Evaluate
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AMALIA - Creation of the Large-Scale Language Model of the Portuguese Language of Portugal (Automatic Multimodal Language Assistant with Artificial Intelligence), reference AMALIA, inserted in measure RE
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AMALIA - Creation of the Large-Scale Language Model of the Portuguese Language of Portugal (Automatic Multimodal Language Assistant with Artificial Intelligence), reference AMALIA, inserted in measure RE