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. (Host institution: Iscte-IUL, Portugal) 2. Project title: Machine learning techniques for crosstalk mitigation and new passive optical network architectures. (Host institution: Iscte-IUL, Portugal
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the European Research Council - ERC COG 101088763. The work for this position is in the area of Machine Learning and Natural Language Processing. We are offering We offer a challenging position with the
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of AI machine/deep learning imagery analysis methodologies and Digital twins applied to cultural heritage assets. 8 - Location Workplace: LNEC – National Laboratory for Civil Engineering, I.P. Avenida do
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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implementing data services; developing intuitive and interactive graphical interfaces; integrating 3D visualization tools with a focus on emerging technologies such as AR and VR; applying machine learning-based
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Analysis and Decision Support - Applying statistical and machine learning methods to interpret the data, identify trends for optimizing aquaculture conditions.; • Experimental Validation - Conducting
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will develop a new high-precision digital twin for WDS based on a self-calibrated hydraulic model with a machine learning correction model and, together with advanced data analytics, will detect and
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of the Grant are:; 1) To apply machine learning algorithms for the diagnosis of faults and malfunctions in photovoltaic plants, using data from SCADA systems combined with synthetic data from digital twins (DT
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for applications for one research grant within the framework of project ISA4RL - Integrating Instance Space Analysis with Auto-Reinforcement Learning for Adaptive Algorithm Selection and Configuration
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-vision algorithms with edge-computing processing for the automatic detection of non-conformities. Machine-learning techniques will be applied to optimize cutting parameters, and the module will be