The mission of the WRAIR Sleep Research Center (SRC) is to characterize the relationships between the features of normal and abnormal sleep and waking performance with the goal of optimizing military readiness.

Specific goals relevant to the present position include: 

·         To use novel analytic approaches to extract signals from multidimensional datasets (principally high density EEG/MEG, also ECOG, MRI) acquired during normal and abnormal sleep. These approaches should provide information that is more informative than traditional sleep staging or spectral analysis.

·         To relate patterns identified in this way to indices of waking performance, perceptual and motor function, cognitive function, alertness, creativity. 

·         To evaluate the effects of interventions - drugs, transcranial electrical stimulation, sleep deprivation/restriction - on these relationships

·         To use patterns derived in this way to characterize the function of REM and NREM sleep, and to delineate states of consciousness and the transitions between these states (sleep onset, awakening, REM-NREM transitions).

The WRAIR SRC engages in the above efforts with the ultimate goal of delivering products (e.g., tools/strategies manuscripts, policy recommendations, etc.) that will optimize laboratory-originated, field-capable technologies to enhance performance of Soldiers and Military Leaders. 

Individuals interested in cutting-edge applied research (including translational neuroscience) are encouraged to apply.  

Candidates should be interested in developing novel approaches for the analysis of multidimensional datasets acquired during normal and abnormal sleep, in association with collaborators and designated experts; incorporating these routines into packages/pipelines, implementing these in the WRAIR SRC environment, and providing instruction and guidance to users; using these methods to address research questions congruent with the SRC mission, writing manuscripts and presenting results at national and international conferences.   

Desirable skillsets include: experience with analysis and interpretation of human imaging data; proficiency in one or programming languages, including Python, Julia, Bash/shell scripting, R, Stan, MATLAB, etc; experience with one or more of the following: signal processing methods; feature classification (e.g. neural networks, self-organizing maps, SVM, HMM); time series analysis; nonlinear dynamics; dynamic connectivity analyses; graph theoretic analysis; Bayesian modeling; topological data analysis; data mining; experience with specialized analysis platforms (e.g. EEG Lab, Fieldtrip, MNE, AFNI, Freesurfer, SPM, TensorFlow, etc.) is preferred but not required. 

key words

EEG; FMRI; Human Imaging; Sleep; Signal Processing; Neuroscience; Cognitive Neuroscience; Translational Neuroscience; Computational Neuroscience;

Citizenship:  Open to U.S. citizens, permanent residents and non-U.S. citizens

Level:  Open to Postdoctoral and Senior applicants