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the form of a human-expert informed reward function. Second, we aim for the integration of low-energy machine learning algorithms, so that the resulting AI model can run on a variety of devices, including
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machine learning algorithms, so that the resulting AI model can run on a variety of devices, including UAVs (e.g. drones) that may be used in turbine inspection. The overall aim is the design of a portable
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working with researchers developing new brain stimulation methods, you will contribute to developing closed-loop algorithms for regulating brain dynamics with clinical applications in epilepsy and
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segmentation algorithms to explore the interconnections within the oral cavity and vocal tract. Designing predictive AI-driven models based on external observations for critical functions like speech and food
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segmentation algorithms to explore the interconnections within the oral cavity and vocal tract. Designing predictive AI-driven models based on external observations for critical functions like speech and food
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to design modular algorithms for complex probabilistic inference with guarantees in the presence of constraints and heterogeneous data. This will require devising novel and efficient algorithms to learn