Research Assistant (ETS) | Temporary

Emory University • Atlanta, GA

9h • Hybrid

About The Position

Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future. We welcome candidates who can contribute to the excellence of our academic community. This position will be part of the Emory Center for Infectious Disease Modeling & Analytics and Training Hub.

Requirements

• 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 β-amyloid (Aβ) 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.

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 β-amyloid (Aβ) 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.

What This Job Offers

• Career Level: Entry Level
• Education Level: No Education Listed