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Responsibilities: Electrochemical process on interface phenomena Battery testing under different conditions Simulation of scaled up process. Interface with machine learning group on data base set up Battery safety
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Responsibilities: Conduct research in the domain of real-time scheduling and resource allocation problems for machine learning pipelines deployed in safety-critical cyber-physical systems. Provide implementation and
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and Data Analytics in Air Traffic Management Systems. The selected candidate will work on developing innovative optimization and Machine Learning models to address key challenges in the future airspace
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of machine learning, simulation-driven testing, and iterative calibration based on real-world datasets. Contribute to scholarly publications, technical documentation, and progress reports required by funding
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., • Interest in developing risk prediction models via deep learning/machine learning. • Have strong background in DL, EEG data and programming for the implementation of proposed methods. Apply now
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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-language-action learning, enabling seamless integration from human instructions to robotic actions in complex mobile manipulation scenarios. Qualifications • Ph.D. Degree in a relevant discipline, e.g
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diseases such as neurodegenerative disorders and psychosis. Statistical, computational, and machine learning methods are developed to analyze and fuse multimodal neuroimaging data. By integrating
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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diffusion models using path integral formulations. This project aims to advance quantum machine learning by: Designing a quantum counterpart of diffusion models; Leveraging path integral methods to model