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models to characterize lung cancer based on a non-invasive methodology. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning
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of the art knowledge in machine learning regarding methods for neural networks complexity reduction ; - development of methods for the evaluation of biases, fairness, overestimation and related metrics
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. OBJECTIVES: - Expand the state of the art in the scientific field of smart buildings and digital twins; - Identify and select appropriate methods for building energy flexibility modelling and optimization
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holders" (https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Expand knowledge of the state of the art in
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RISC-V processor, using HLS tools; - Compare the implementation with state-of-the-art RISC-V simulators or cores; - Optionally, add to the implementation the ability to specify extensions to the base
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holders" (https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Expand knowledge of the state of the art in
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TEC. 2. OBJECTIVES: - Enlarge knowledge of digital simulators state-of-the-art for power systems; - Develop the R&D capacity through the application of machine learning methods; - Develop research
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: Measure the impact of the orchestration strategies on application performance, resource utilization, and energy efficiency.; 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - Literature Review: In
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to grant holders" (https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Expand the state of the art in
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of the art knowledge in machine learning regarding methods for neural networks complexity reduction ; - Development of methods for the evaluation of biases, fairness, overestimation and related metrics