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, that combines diffusion and transformer models, there are clear indications that the analysis of this data can be automated. This will open new avenues in data interpretation and building predictive models
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30 Aug 2025 Job Information Organisation/Company KU LEUVEN Department Robotics, Automation and Mechatronics/Engineering Technology Research Field Engineering » Mechanical engineering Researcher
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to financial operations Develop systems for automated regulatory compliance checks, fraud detection, risk analysis, or smart contract orchestration Investigate the integration of agentic reasoning with financial
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properties of the cluster-substrate system using an automated photocatalytic gas test setup for CO2 photoreduction available at A-PECS. Importantly, the PhD candidate will thus receive a joint PhD degree by
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for anomaly Detection and diagnostics: Leveraging state-of-the-art machine learning and deep learning models for automated fault detection, classification, and time-till-failure prediction. This will involve
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visual behavior, visual circuit development, and automated behavioral assays. Methodologies include: Innate visual behavior assays using naturalistic visual stimuli (e.g. looming threats, prey-like
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visual behavior, visual circuit development, and automated behavioral assays. Methodologies include: Innate visual behavior assays using naturalistic visual stimuli (e.g. looming threats, prey-like
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here: https://edu.lu/wwpy7 Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas, in collaboration with the Automation and Robotics Research Group, led
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and a willingness to further develop those skills to automate your data processing and improve your own workflow efficiency are expected. You have a strong interest in catalysis and structure-function
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properties of the cluster-substrate system using an automated photocatalytic gas test setup for CO2 photoreduction available at A-PECS. Importantly, the PhD candidate will thus receive a joint PhD degree by