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Field
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of AI for the integration of multimodal healthcare data specifically incorporating patient preferences. This includes investigating new methods but also designing and benchmarking integration algorithms
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designing and benchmarking integration algorithms. The position is situated in the Intelligent Data Engineering Lab and will be supervised by Dr. Jan-Christoph Kalo and Prof. Paul Groth. What you will do
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responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with stakeholders Development of open
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-board Payload Signal and Data Processing algorithms and techniques for RF payloads and instruments in close collaboration with TEC-ED; and Time and frequency references, modelling, design tools
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learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning for computer vision
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and Mission Science team located at ESTEC (Noordwijk, Netherlands) to align the development of AI-driven methodologies and algorithms with the CHIME mission. Technical competencies Knowledge relevant
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system-level grid-connected LDES models for grid support Research, design and development of control algorithms for optimal operation of grid-integrated LDES; Develop a co-simulation framework to analyse
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data, complicated algorithms are required. Some of these algorithms are yet to be developed and/or validated, with real data from polar regions required in order to do so. A dedicated airborne radar
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science and societal application. We contribute to innovative information technologies through the development and application of new concepts, theories, algorithms, and software methods. With our expertise
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: designing and developing prototype algorithms for ground processing of Synthetic Aperture Radar images, with a focus on X-band systems; developing Synthetic Aperture Radar image processing; validating and