Image segmentation and nuclei identification using deep learning

C. elegans embryos are powerful model systems for studying developmental variation using microscopy because they are transparent and can be fluorescently marked. However, automatic detection/segmentation of fluorescently marked nuclei is a challenging image informatics problem. This rotation would consist of applying deep learning techniques to this problem based on a corups of images that have been previously manually curated. Experience with python is useful and previous exposure/experience with deep learning would also be useful.