Research Assistant (ETS) | Temporary

Emory•Atlanta, GA

1d•Onsite

About The Position

This position will be part of the Emory Center for Infectious Disease Modeling & Analytics and Training Hub. The role involves two main projects: Project 1 focuses on Data Curation & Pipeline Specialist (Shedding Hub), involving literature searches, AI-driven data extraction, quality control, and schema management. Project 2 focuses on Data Analyst for Electrophysiological & Alzheimer’s Disease Research, including clinical data extraction, EEG preprocessing, feature extraction, statistical analysis, and manuscript drafting for publication.

Requirements

Experience with biomedical databases and literature search techniques.
Familiarity with AI-powered data extraction pipelines.
Proficiency in data quality control and validation.
Experience with data schema and controlled vocabulary management.
Ability to extract, manipulate, and organize clinical data and EEG records.
Experience with EEG preprocessing and data manipulation.
Skills in feature extraction for biomarker identification.
Proficiency in statistical modeling and analysis.
Experience translating complex data into visualizations.
Ability to interpret statistical results.
Contribution to drafting manuscripts for peer-reviewed publication.

Responsibilities

Conduct systematic and targeted literature searches across biomedical databases to identify relevant datasets and publications focused on pathogen shedding.
Utilize and maintain the department’s existing AI-powered data extraction pipeline to harvest, aggregate, and cumulate complex biological datasets.
Perform rigorous quality control reviews on AI-extracted data to ensure high accuracy, completeness, and alignment with open-science standards.
Actively update, refine, and maintain the project’s data schema and controlled vocabulary (ontologies) to support standardized data integration.
Extract, manipulate, and organize raw clinical data and EEG records securely from the clinical server.
Oversee the data preprocessing pipeline for electrophysiological data modalities, handling diverse data formats and utilizing specialized toolboxes.
Execute feature extraction to identify quantitative EEG (qEEG) biomarkers among patients diagnosed with Alzheimer’s Disease and Mild Cognitive Impairment (MCI).
Conduct robust statistical modeling to compare identified qEEG biomarkers against existing diagnostic standards, including $\beta$-amyloid (A$\beta$) and tau protein levels, as well as Montreal Cognitive Assessment (MoCA) scores.
Translate complex sensor data into clear visualizations, interpret statistical results, and heavily contribute to drafting a manuscript for publication in a peer-reviewed clinical journal.