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project, particularly the Digital Planet activity which supports the analysis of large-scale data from a variety of sources. This data analysis can include using distributed machine learning techniques
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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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INESC TEC is accepting applications to award 1 Scientific Research Grant - HfPT - CBER (AE2024-0180)
16 May 2024 Job Information Organisation/Company INESC TEC Research Field Computer science » Computer systems Engineering Researcher Profile First Stage Researcher (R1) Country Portugal Application
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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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defined functionalities and characteristics to be able to acquire specific movement data. This work involves 5 phases: 1) designing the architecture of the wearable system 2) designing the device in CAD
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18 Apr 2024 Job Information Organisation/Company INESC TEC Research Field Computer science Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Country Portugal
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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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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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3 May 2024 Job Information Organisation/Company INESC TEC Research Field Computer science » Programming Computer science » Computer systems Computer science » Informatics Researcher Profile First
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requirements: Masteer's Dgree in Electrical and Computer Engineering and related areas The awarding of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher