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are urgently needed to monitor PFAS in water and probe their interactions with biological systems. This PhD project will develop a cutting-edge single-molecule optical sensor for real-time, ultra-sensitive PFAS
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will apply nonlinear and associational (colloquially called “causal”) timeseries analysis techniques to provide a more rigorous, and more statistically significant framework for understanding
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well as retinal fundus images, we will explore analysis of new eye image datasets including OCTA and CCM images for diagnosis of diabetic neuropathy Machine Learning: We will develop artificial intelligence (AI
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. Additionally, missions like Landsat optical, Sentinel-1 SAR and Sentinel-2 optical enable time-series observations, important as spectral signatures changes after a storm disturbance. Commercial datasets (e.g
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investigate various stress parameters to reveal cryptic consequences of the selfish chromosome of Drosophila testacea, chosen for its newly-described genetic tools allowing individuals to be genotyped by eye