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Field
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for representing and combining multimodal information over time. Grounded in machine learning, representation learning, and efficient algorithms, the work addresses real-world challenges in sustainable and
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and EU-funded research projects, and has extensive know-how in 5G/6G communication platforms, IoT platforms, and Demand Response algorithms for the Smart Grid. IQU is also active in many EU-funded
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. Expect close collaboration with industrial experts and the opportunity to see your algorithms influence aerospace and other high-value manufacturing sectors. Funding and eligibility 3-year, full-time PhD
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analytics, anomaly detection, and embedded redundancy to enhance system resilience. Students will focus on creating adaptive algorithms and hardware implementations that enable real-time diagnostics and
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funded by the Research Council of Norway (2025-2030). The primary objective is to create a new generation of algorithms for inference and decision-making by pushing the boundaries of the underlying
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. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also expected
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, epidemiological data and outcome modelling using AI-assisted algorithms, as well as multi-modal data integrations. An established data infrastructure with expertise and computational pipelines for these analyses
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underexplored. To this end, the project will explore the application of the next generation of deep learning algorithms, e.g. self-supervised learning techniques, particularly suited to infrastructure
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on the complementary expertise and recognized excellence of its 22 research teams to contribute to the development of the fundamental aspects of computer science (models, languages, methods, algorithms) and to foster
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, under the scope of a term contract, with a termination date undetermined, overseen by Portuguese Labour Code. Job description: Contribution in WP3 Task 3.3 aiming to define compressed sensing algorithm