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of advanced Federated Learning algorithms. The research activity will be aimed at the study, implementation, and validation of distributed learning solutions. Where to apply Website https://pica.cineca.it/unina
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Overview We are seeking an experienced researcher to lead the development of decentralised swarm mapping and localisation algorithms for underground pipe operations as part of an international
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Are you an ambitious researcher in machine learning, swarm robotics, multi-robot systems, distributed AI or autonomous systems looking to lead internationally significant work? We have an exciting
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courses such as geographic databases, Web GIS, GIS algorithms and data structures, geospatial artificial intelligence (GeoAI), and the collection and analysis of 3D geodata. The position includes course
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. The successful candidate will contribute to the design and implementation of algorithms, symbolic computation systems, data processing pipelines, and machine learning. Essential Job Duties Develop computational
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. Prepare, distribute and utilize instructional support materials, including course syllabi, supplementary materials, instructional media and other devices as appropriate. Convene classes as scheduled and
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for the manufacturing sector, focused on regenerative models and operator-machine interaction with a view to Industry 5.0. Algorithms will be studied for the personalized adaptation of interactions, improving efficiency
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Mission: Support research to improve the management of renewable energies. Functions to be developed: Develop machine learning algorithms. Implement and validate computational models. Plan networks with
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and/or Windows environments Working knowledge of modern development tools (Git, CI/CD pipelines, automated testing frameworks) Knowledge of data structures, algorithms, and performance optimization
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maintaining software in Linux and/or Windows environments Working knowledge of modern development tools (Git, CI/CD pipelines, automated testing frameworks) Knowledge of data structures, algorithms, and