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This work will be performed in service of creating a new surgical device for lifesaving emergency airway access in the ER, by EMS and on the battlefield. Our ultrasound team is looking for students who can assist with image rendering, computer vision, and machine learning. We are particularly interested in candidates who have some experience training neural networks for object detection, classification, and semantic segmentation. Candidates should have experience developing machine learning pipelines that include data preprocessing, data augmentation, adapting from existing models or developing new models, turning parameters and hyperparameters for training and testing, and performing sensitivity analysis of model performance. Candidates should have proficiency in python and have experience using packages such as PyTorch.

This research will be a collaboration between the engineering and medical school and is a great opportunity to work on technology that will be used on patients during the semester. You will be part of the product development process.