36 molecular-modeling-or-molecular-dynamic-simulation Fellowship positions at INESC TEC
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the fact that security and data breaches in AI systems can progressively affect the quality of future decisions ; - Development of a simulation system that allows, through a disturbance agent, the
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with simulation techniques, energy efficiency models, large-scale energy consumption data, machine learning techniques and interpretation (unsupervised); - Education, experience and research orientation
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the modelling and control of microgrids Previous experience in real-time simulation and Power Hardware In the Loop test systems. At least one paper in conference or journal. Minimum requirements: Solid experience
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of the institution's charging infrastructure.; • Contribute to the development of energy metering modules.; • Explore and implement software solutions for communicating metering data between devices.; • Design, simulate
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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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, 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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results); Implementation of the hardware interface between the RISC-V core and CGRA, either in hardware (via HLS or HDL) or via a co-simulation system ; Contribute to or use a binary generation method for
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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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Education Institutions. Preference factors: - Knowledge of fundamental concepts related to energy management and gas networks; - Knowledge of optimization and forecasting models; - Knowledge of Python