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increasingly complex networks. By deploying and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection
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military performance, presenteeism, and may even lead to costly evacuations during deployments. This PhD project builds upon pioneering research at MHQA and aims to implement and evaluate allergy screening
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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. Kinetic rates will be calculated on the fly from molecular dynamics simulations using machine learning potentials. This approach will provide guidelines to steer the formation process of zeolites by tuning
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laude level. You are interested in both Machine Learning and Symbolic/Logic-based AI methods. You strive for excellence and have a scientific mindset. You are a loyal team player, who can work
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knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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» Science communication Computer science » Other Engineering » Design engineering Technology » Computer technology Technology » Future technology Arts » Visual arts Computer science » Informatics Researcher
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information about the role, please contact Prof. Radu State Your profile Strong background in AI, machine learning, or multi-agent systems, ideally with interest in financial systems, decentralized ledgers