Performs research focused on EEG data processing and biomarker development to improve early interventions in first-episode psychosis (FEP). The role centers on developing EEG-based predictive models for treatment response to antipsychotics and neuromodulation therapies. Research expertise in EEG preprocessing, artifact rejection, and feature extraction using MATLAB and / or Python; experience with functional connectivity analyses (e.g., coherence, PLI, imaginary coherence, graph theory); and a strong background in statistical modeling, including machine learning techniques (Lasso, Ridge regression, random forests), linear mixed-effects models, and cross-validation in R or Python. Familiarity with clinical trial data in schizophrenia or depression is expected, along with the ability to independently set up and maintain EEG hardware, design task-based paradigms, and integrate EEG with multimodal data across longitudinal studies. The researcher will join a multidisciplinary team working on projects such as decision-support tools for clozapine initiation, EEG predictors of aggression in schizophrenia, and biomarkers of treatment response to ECT, TMS, and psychedelics.
Requires : Dual MD / PhD with meaningful experience in EEG and psychiatric disorders - preferably schizophrenia.
Salary : $58,539.98 - $92,649.96.
Post Research • Glen Oaks, NY, United States