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courses of Higher Education Institutions. Preference factors: • Experience with computational simulation models / MATLAB/Simulink.; • Knowledge of industrial-grade communication protocols (Modbus TCP, IEC
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developing synthetic datasets using simulation environments. Familiarity with the theory and implementation of diffusion models and GANNs applied to the same context. Minimum requirements: • Knowledge
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to variable external loads:; i. Analysis and modeling of the robotic manipulator and the devices to be integrated (end-effector), defining the relevant mechanical and control parameters.; ii. Development
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of this project is to create a radiomics and radiogenomics based approach to describe and create predictive models to characterize lung cancer based on a non-invasive methodology. 3. BRIEF PRESENTATION OF THE WORK
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-of-the-art deep neural networks for musical audio, with special focus on timbre analysis and manipulation.; - Identify and implement approaches for explainable ML models.; - Cooperate in writing scientific
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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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/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: The overall vision of the ATE is to deploy and demonstrate a set of business models
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architectures for the energy and power management system on ships Develop control and dispatch strategies for hybrid microgrids, taking into account the specific power and energy requirements of ships Modeling