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relate to processing-relevant traits such as fry quality, yield, and waste? The project will take an integrated approach combining advanced imaging, quantitative phenotyping, and genetics. A high
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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cancer prevention and improved survivorship. The project advances a paradigm shift: transport is no longer a source of negative impacts – such as safety issues and adverse health effects, but rather a
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contests to facilitate the generation, development, and implementation of new products, services, processes, and business model ideas. However, out of a pool of submitted ideas, typically only a few will be
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sustainable machine learning approaches and addressing renewable energy related projects. Likewise, deploying a novel paradigm of KGML (knowledge guided machine learning) can propel further research. PhD
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, substation, corridor scenarios) Integrate physics-informed machine learning models with signal processing feature extraction Develop prototype software tools for automated waveform analytics and real-time
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, actuation, and control. The research includes the design, fabrication, and experimental validation of micro-scale robotic platforms, integration of optical and imaging-based feedback, and development
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force behind the design, construction, and experimental validation of a next-generation magnetocaloric heat pump prototype, a technology poised to revolutionize the market and contribute significantly
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novel strategies to treat seizures and cytotoxic edema, especially in neonates. To reach this goal, we are addressing the following questions: 1. How does the brain inhibitory system work at the cellular