Description
A postdoctoral position is available in Prerau lab (sleepEEG.org) within the Division of Sleep and Circadian Disorders in the Department of Medicine at Brigham and Women’s Hospital and Harvard Medical School. The primary goal of this position is to use advanced statistical modeling techniques, in particular point process models, to better understand the relative influence of neural mechanisms on sleep spindle dynamics in the context of natural aging, neurodevelopment, and neurodegenerative disease.
The ideal candidate will hold a PhD in mathematics, statistics, biostatistics, computational neuroscience, or computer science. Direct experience and a history of publication in research involving EEG signal processing, sleep data analysis, spectral analysis, and point process modeling within a generalized linear model (GLM) framework are strongly preferred. Strong computer programming skill in MATLAB is required. Salary and fringe benefits commensurate with experience will be provided in compliance with approved NIH standards.
Interested candidates should send 1) a personal statement including a description of research interests, 2) three potential referees, and 3) a Curriculum Vitae to Dr. Prerau (mprerau@bwh.harvard.edu).
About Prerau Lab: Our laboratory focuses on understanding the relationship between brain dynamics during sleep and neurological dysfunction, with the goal of biomarker discovery for diagnosing and treating neurological, psychiatric, and sleep disorders. Our lab also explores how brain activity patterns are highly specific to individuals, contributing to a deeper understanding of individual differences in brain function. We aim to advance our understanding of brain health and disease through cutting-edge quantitative analyses and experiments, striving towards improved diagnostics and treatments.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.