• 124
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20182023

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Driven by organic neuromorphics to achieve autonomous on-chip learning

Academic background

After completing her Bachelor in Applied Physics on the topic of magnetization reversal in cobalt wires she continued her physics Master interested in various topics. In particular drawn to the medical applications of physics she did a research internship at the Swinburne University of Technology in Melbourne, Australia, where she studied the cell uptake of ligand functionalized gold nanospheres using high-order image correlation spectroscopy. For her graduation project she went to the University of Minnesota in Minneapolis, USA, to investigate the morphology and the effect of plasma on the gas flow in cold atmospheric pressure plasma jets impinging on a substrate. She got excited by the combination of research and the application of technology for medical purposes and joined the neuromorphic engineering group in January 2019. Her goal is to create a microfluidic chip with integrated sensors able to detect and classify biological cells using machine-learning.

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