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Field
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nuclear and particle physics research leveraging machine learning and AI for data analysis and detector development, as well as exploratory work in quantum algorithms, depending on background and interests
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-sensor fusion, and propagation modeling — to develop AI-enabled detection, classification, and triangulation algorithms for critical energy infrastructure applications. This position resides within
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operations. The PhD will develop and implement artificial intelligence and data-driven methods for early anomaly detection, root cause diagnosis, and failure prediction on industrial systems, leveraging
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systems. Key Responsibilities Develop graph-based (multi-)omics analysis algorithms Benchmark graph-theoretic against graph-ML approaches Analysis of food-related (multi-)omics data Your Profile The ideal
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not originally designed to manage large numbers of flexible and decentralised energy resources. This PhD project will develop new AI-driven methods for operating smart distribution networks so that
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the likelihood of the target to fall within the stationary clutter returns and in the shadow of complex structures. We will investigate the use of multistatic radars against low observable threats and develop
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flow reconstruction, enabling both real-time coarse diagnostics and high-fidelity offline velocity field estimation. Developing reinforcement learning (RL) algorithms for a multi-agent robotics system
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Integration: This WP develops a Runtime Assurance Layer by deploying lightweight anomaly detection algorithms, such as autoencoders, to flag unsafe AI decisions. It also involves the development of an Ethical
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28 Feb 2026 Job Information Organisation/Company Tilburg University Research Field Mathematics » Algorithms Mathematics » Applied mathematics Researcher Profile First Stage Researcher (R1
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will develop algorithms and test them in an advanced, automated microbial feedback control laboratory, enabling rapid iteration from concept → implementation → experimental validation. These PhDs sit