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the preparation of technical reports on the algorithms, mechanisms, models, or protocols developed; - collaborate in the development of new communications solutions for extreme environments; - contribute to co
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interfaces (HMI), and industrial-grade communication protocols for automation in electric power systems.; • Develop and adapt a test network — a simulation model or a replica of a real network — for DIgSILENT
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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
; - survey and analyze the state of the art in emerging wireless networks, including simulation aspects; - collaborate in the preparation of technical reports on the algorithms, mechanisms, models
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; 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - Identify state-of-the-art Vision-Language Models for image captioning; - Benchmark the models in occlusion scenarios; - Cooperate in writing
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industrial-grade communication protocols for automation in electric power systems.; Implement the interface between OPAL-RT and HMI/SCADA software: connecting the real-time model or digital twin with the SCADA
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, energy consumption, and accuracy.; ; Training deep learning models, especially in LLMs, faces critical challenges that compromise the optimal use of GPUs. These bottlenecks result in poor computational
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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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: - prepare the requirements specification for a software module that allows the use of pre-trained large language models (Large Language Model); - containerization and availability of trained models
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workload’s data (e.g., Deep Learning, Large Language Models) while addressing the I/O interference and fairness challenges faced by current distributed infrastructures, where storage resources are being shared
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Education Institutions. Preference factors: - Knowledge of fundamental concepts related to energy management and gas networks; - Knowledge of optimization and forecasting models; - Knowledge of Python