Identification of biological cell features using computer vision and deep learning
Motivation and Scope
Image-based cell profiling in biology has been demonstrated to be useful for many activities including discovering potential medicines and determining the effect of a chemical on cells - whether beneficial or harmful. This project will investigate recent advances in computer vision and deep learning that better leverage image-based information and that have the potential to accelerate often laborious and expensive chemical testing processes.
This project will apply state-of-the-art machine learning algorithms to cell imaging datasets to identify important features that can be used to improve image-based cell profiling techniques.
Good programming skills, with knowledge of image processing, computer vision and/or machine learning.
This project will provide experience in working with state-of-the-art computer vision and machine learning algorithms, and applying them to an important and relevant scientific problem.