The Laboratory of Integrated Brain Imaging (PI: Dr. Zhongming Liu) has multiple positions available for undergraduate and graduate students to work for research during Summer 2021. As a temporary worker (or a summer intern), each student will be paid for on an hourly basis. Preference will be given to the students who are likely to extend the work to Fall 2021 or research for master thesis.
Job 1: Animal MRI image analysis
The student will work with the PI and existing graduate students to develop and test an MRI image processing pipeline for automated analysis of gastrointestinal MRI. The pipeline to be established will include image denoising, co-registration, motion correction, segmentation, 3D surface modeling, rendering. A strong candidate should have strong programming skills (Python and Matlab), knowledge with image and signal processing and optimization, good work ethics and commitment to teamwork. An ideal candidate should have experiences with machine learning, especially deep learning (using PyTorch).
Job 2: Animal fMRI analysis pipeline
The student will work with the PI and existing graduate students to develop and test a processing pipeline for online and offline analysis of animal fMRI images. The pipeline to be established will include image denoising, filtering, motion correction, co-registration, segmentation, surface modeling and rendering, as well as statistical parametric mapping with linear regression, statistical tests, principal or independent component analysis, functional connectivity etc. A strong candidate should have strong programming skills (Python and Matlab), knowledge with image and signal processing, optimization methods, good work ethics and commitment to teamwork. An ideal candidate should have knowledge with either animal or human brain mapping, system neuroscience.
Job 3: Representation learning of fMRI activity
The student will work with the PI and existing graduate students to develop, test and document deep learning methods for representation learning of human brain activity. The methods to be developed will include deep learning with neural networks, e.g., variational autoencoder, recurrent neural networks, Transformer, graph neural networks. Part of this job will involve documentation, testing, and application of existing methods already developed in the lab. A strong candidate should have strong programming skills, prior experiences with deep learning (PyTorch or TensorFlow) in the context of medical image analysis, computer vision or natural language processing, good work ethics and commitment to teamwork.
Job 4: Animal MRI and electrophysiology
The student will need to work in the lab and assist in vivo animal experiments that involve animal (rodents) MRI, neuromodulation, and electrophysiology. A strong candidate should have interest and background in biomedical engineering and neuroscience. An ideal candidate should have prior experiences with animal handling, surgery, behavioral testing, electrophysiology. Experiences with data analysis and programming are desirable but not required.
For any inquiry, please contact Dr. Zhongming Liu (firstname.lastname@example.org).