The Georgia State University/Georgia Institute of Technology/Emory University Center for Translational Research in Neuroimaging and Data Science (TReNDS) is focused on developing advanced analytic approaches and neuroinformatics tools that leverage brain imaging data, with a goal of translating these approaches into biomarkers that help solve issues related to brain health and disease. Large-scale data sharing and multimodal data fusion techniques are the underpinnings of our approach. We develop state-of-the-art signal processing and web-based solutions to further this goal.
About the Team
Georgia State University’s new Center for Translational Research in Neuroimaging and Data Science (TReNDS) is looking for a post-doctoral associate to join our machine learning core team to engage students in learning the technical skills that industry increasingly expects from Data Scientists. Big Data comes from the Internet of Things (IoT), robotics, autonomous vehicles, and other IT-related fields such as scientific labs working with medical or remote-sensing data, companies specializing in big data processing and analysis, cloud storage and computing services.
About the Role
The Post-Doctoral Associate in this position will work in a multi-disciplinary and multi-institutional collaborative environment developing models capable of learning from high-dimensional brain imaging data and transfer to application settings where labels are rarely available and data is usually scarce. The person in this position will work under the supervision of Dr. Sergey Plis, Associate Professor in Computer Science and Director of the TReNDS Machine Learning Core.
Primary Duties and Responsibilities
– Develop novel deep learning models for 3D and 4D image processing with application to brain imaging and a focus on building robust and easy to use models.
– Joining our group you will work in a multi-disciplinary and multi-institutional research team on developing models capable of learning from high-dimensional brain imaging data and transfer to application settings where labels are rarely available and data is usually scarce.
– Your tasks include conducting original research on the development of these models, and unsupervised, or self-supervised ways to train them, publish papers on your findings at machine learning conferences and in brain imaging journals, work with PhD students from GSU, GATech, and Emory (with an opportunity to co-supervise), and mentor developers working on implementing distributed training of these models.
Preferred Hiring Qualifications
– PhD or equivalent in computational fields and/or experience with biomedical data are required.
– Strong quantitative background, computational and analytic, and programming experience in python.
– Understanding of the relevant literature
– Ability to conduct research reflected in a publication record.