Help unlock the linkage between sleep and the pathophysiology of psychiatric and neurodegenerative disorders.
Our group, under Dr. Michael Prerau, is developing state-of-the-art techniques in statistical signal processing algorithms to understand the dynamics of brain activity during sleep and to identify robust biomarkers for psychiatric and neurodegenerative disorders. We are looking for exceptionally self-motivated and creative people with a strong background in computer science, statistical modeling, and signal processing to help us change the way people look at sleep and brain health.
The research assistant should have extensive programming experience in MATLAB, and experience with python, C/C++, HDFS/Hive/Spark is a plus. They should hold at least bachelor’s degree in biomedical engineering, computer science, data science, computational neuroscience, mathematics and statistics or related fields. They should have knowledge of signal processing and analysis and possess an interest in sleep and neuroscience. Previous experience with EEG analysis, data visualization, and spectral analysis is also highly desirable.
The Postdoctoral fellow should hold a PhD degree in mathematics and statistics, biomedical engineering, computer science, data science, computational neuroscience, or related fields, and have a deep interest in learning the neural mechanisms of sleep and disease. The fellow should be a self-motivated and independent worker, with a history of publication and an interest in the neural mechanisms of sleep and neurological disease. They should have extensive experience with programming, signal processing and statistical modeling for neural data—previous experience with state-space modeling, point process analysis, and EEG source localization will enhance competitiveness. Experience with EEG recording and experimental procedures is a plus.
Interested candidates should send a CV and cover letter to email@example.com.