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My research connects stars, dust, and gas, with the goal of building a unified multidimensional picture of the Milky Way and nearby galaxies. I am particularly interested in the lifecycle of matter
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approach that ensures both stealth and functionality. This project proposes to develop Stealth Integrated Sensing and Communication (Stealth-ISAC), a paradigm where communication and sensing signals remain
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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