AI assisted biosensors have been widely used in broad areas to improve the accuracy of diagnosis recently. For examples, assistive recognition in sonograms, MRI, CT scans, and LC-MS. With the assistance, immense data can be processed and minor details can be well examined for more valuable information. Over the past years, BMOEMS lab has developed several sensing techniques that can greatly enhance the existing sensitivity, accuracy, cost, and time-efficiency. One of them is Janus particle (JP) enabled optical diffusometry. By functionalizing the JPs with antibodies or aptamers, we are able to detect the presence of disease biomarkers by the blinking signal generated from the JPs. The blinking frequency is subject to particle diameter, fluid viscosity, and ambient temperature. Therefore, JPs can serve as multifunctional probes to detect the dynamic changes of their environment. Based on this technology, we would like to employ AI to raise data rate and mitigate uncertainty. To this end, this internship is seeking talented students whose major is associated with electrical engineering, informatics, biomedical engineering, or basic medicine.

The internship will last for three months along with comprehensive lab training, English-friendly lab environment, lab accessibility, and equal lab benefits. The interns are required to participate in all BMOEMS lab activities and complete assignments related to their project. A mentor-mentee program will also be applied to assure them of adapting to the lab life rapidly and smoothly. Outstanding interns will be eventually invited to continue their postgraduate studies with us after the internship as well.