Summary

This two-year postdoctoral fellowship is being offered as part of an NIMH R21 award to study the utility of EEG gamma oscillations as a stratification tool for patients seeking ketamine therapy for major depressive disorder. The fellow will work closely with the MPI’s to develop a rigorous analytical framework based on temporal, spectral, and non-linear approaches to interpreting variability in NMDA receptor antagonism as it relates to ketamine treatment outcome. The objective of the fellowship is for the trainee to develop a strong portfolio of scientific work that will support either a future K-award application or a transition to a related industry position. 

Job Duties

• Works with the research team to manage the recruitment of patients. 
• Collects EEG data from patients at our partner clinic location. 
• Analyzes EEG data and prepare findings for publication, and presentation at national and international conferences. 
• Manages data archiving for NIH reporting. 
• Engages in collaborative research activities with other trainees and faculty within the department of psychiatry 
• Engages in non-didactic teaching activities, including the mentoring of undergraduate research assistants, presentations at journal clubs, and skills demonstrations within the department. 
   

Minimum Qualifications

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

Preferred Qualifications

• PhD in neuroscience, experimental psychology, engineering, computer science, physics, or related field. 
• The candidate should have experience with collecting and processing biological signals (M/EEG [preferred], EMG, EOG, ERG). Human experience is preferred but exceptional animal research skills will be considered. 
• Working knowledge of scientific computing languages, including Matlab (preferred), Python, R. 
• Experience with experiment presentation software (EPrime, Presentation) preferred but not required. 
• Experience with server computing in the Linux environment (preferred but not required).