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and optimisation algorithms, focusing on their practical application in the context of the RaceEngineerAI project. Tasks include: - Developing models capable of simulating the behaviour of racing
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 15 days ago
for Science and Technology, I.P., both in their current wording. 2. Activity objective: Research and implementation of advanced Optimization and decision-support algorithms using Artificial Intelligence applied
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internationally. Main Responsibilities · Contribute to the installation, calibration, and validation of radio monitoring equipment. · Develop and test real-time data pipelines and deep learning algorithms for Solar
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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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of the state of the art in Evolutionary Algorithms and Large Language Models. Survey of the state of the art in Evolutionary Algorithms applied to Large Language Models. Implementation of an evolutionary
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domains. The successful candidate will: Develop algorithms to model team performance based on interpersonal (e.g., monitoring, communication) and cognitive (e.g., shared mental models) processes. Design an
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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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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
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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requirements, as well as the design of data models, synchronisation algorithms and analysis and learning models applied to brain and physiological signals. The objectives of this fellowship are: 1. To survey