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, considering discrete modulation; Contribute to the implementation of digital signal processing algorithms in a FPGA platform; Contribute to the implementation of information reconciliation algorithms in a GPU
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artificial intelligence-based algorithms to optimise operation and predict anomalies in water distribution networks. The algorithms developed should identify patterns and anomalies that indicate the presence
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solutions; • Implementing and comparing different Intelligent Optimisation algorithms. • Implementing, providing and monitoring intelligent solutions (e.g., via API). • Producing documentation
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until the time of signing the contract. Activity Outline: Grant holders will work on the following topics TASK 3: Empirical Analysis of Deep Learning and Generative Modeling Algorithms TASK 4: Development
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to or higher than 16 points. 4. Work Plan: 4.1. The purpose of this contract is to perform the following tasks: Literature review in artificial intelligence algorithms for Fairness in Online Learning algorithms
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Artificial Intelligence, with an emphasis on developing methodologies and techniques for Evolutionary Computation and Machine Learning. Work Plan: State-of-the-art survey of Evolutionary Algorithms and Large
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clinical data and machine learning algorithms. The main activities include: Data Processing: • Collection of historical patient data (demographics, clinical history, outcomes of interventions). Data cleaning
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | 4 days ago
-objective optimization and control algorithms to orchestrate EV charging and discharging in large buildings within a transactive energy framework, coordinating them with stationary storage and other demand
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clinical data and machine learning algorithms. The main activities include: Support for AI Model Development: • Collaborating on the training of predictive models under the supervision of the scientific team
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requirement Work plan: The candidate will carry out R&D activities within the scope of the 2022.06672.PTDC project, namely: 1) Review of the literature on adaptive mesh generation algorithms for singular