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Your Environment. Your Health.

Postdoctoral Fellowship in Machine Learning for Computational Biology/Neuroscience

Department of Health and Human Services
National Institutes of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Biostatistics and Computational Biology Branch
Research Triangle Park, North Carolina

The lab is collaborating with physician scientists who have generated a large amount of human sleep polysomnography data (for over 10,000 subjects), including electroencephalogram (EEG), electromyography (EMG), electrocardiography (ECG), and other types of sleep data. This data also contains clinical outcomes. We have assembled a multidisciplinary team including physicians, statisticians, computer scientist/electric engineers, and bioinformaticians with expertise in deep learning, signal processing, classification, and statistics. Ongoing projects in the lab include brain wave characterization, prediction of sleep stages and disease classification using machine learning approaches including deep learning. For classification, we are interested in identifying features that can distinguish between healthy controls and diseases such as neurological diseases.


Applicants must have a doctoral degree in computer science, electrical engineering, neuroscience, or a related area with less than five years of postdoctoral research experience. Experience with digital signal processing in EEG, speech, acoustics and/or deep learning is highly preferred.

To Apply:

Please send a cover letter, curriculum vitae, and list of three references to Leping Li, Ph.D..

The NIH is dedicated to building a diverse community in its training and employment programs.

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