Postdoctoral Fellow (Data Engineering & AI/ML)

The Geneva Foundation • Bethesda, MD

8d

About The Position

The Post-Doctoral Fellow I supports the Principal Investigator, Co-Investigators, and research staff in conducting research. The role includes supporting protocol adherence, enrollment targets when applicable, monitoring visits, regulatory and administrative work, data management, and project close-out.

The position contributes to a multi-institution collaboration with Stanford, Johns Hopkins, the Veteran Affairs (VA), and the Department of War (DoW) to build a sleep foundation model. The project uses self-supervised learning on petabyte-scale physiological sleep study data to generate data representations (embeddings), with the goal of forecasting future health risks and identifying patterns not captured by traditional sleep scoring metrics.

The fellow designs, develops, and deploys scalable applications and data pipelines for large-scale research, including ETL pipelines for multimodal datasets. The role also supports scalable infrastructure for machine learning, data integrity, technical documentation, research dissemination, and collaboration across the research team. The stated salary range is $65,000–$79,000.

Requirements

• PhD or MD required.
• Five or more years of experience with multimodal data analysis.
• Proven experience with signal processing, such as time-series biosensor data.
• Hands-on experience with version control systems such as Git and ability to work in a collaborative coding environment.
• Experience with cloud computing, or a strong desire to learn it, including managing cloud-native data warehouses and establishing ETL pipelines.
• Ability to work in a fast-paced, multidisciplinary, multi-site team, including asynchronous collaboration.
• Strong oral and written communication skills.
• Organization and attention to detail, with a positive, friendly, and professional demeanor.
• Flexibility with changing priorities and ability to interact with employees, clients, and sponsors at all levels.
• Ability to exercise independent judgment in a fast-paced, high-pressure environment with strict deadlines and manage multiple projects.
• Intermediate-level computer skills, including Excel and other Microsoft Office software.

Nice To Haves

• One to two years of medical research project management experience is strongly desired, preferably with the Department of Defense.
• Strong knowledge of sleep science.
• Familiarity with machine learning workflows, including model development, model tuning, and deploying models at scale.
• Knowledge of military systems.

Responsibilities

• Design, develop, and deploy scalable front-end applications and back-end data pipelines to support large-scale research.
• Build ETL pipelines that ingest multimodal datasets, including wearables cross-referenced with EHRs, PSGs, and subjective sleep metrics, and support efficient storage, retrieval, and processing of datasets exceeding one million records.
• Support the development of scalable infrastructure for machine learning models using physiological features and sleep microarchitectures.
• Optimize application performance and scalability through performance tuning, code refactoring, and database optimization.
• Stay informed about developments in data engineering, cloud architecture, and machine learning to improve the lab’s technical capabilities.
• Ensure data integrity throughout engineering workflows.
• Assist with preparing Standard Operating Procedures, analytical frameworks, and technical documentation.
• Maintain communication with leadership, advise on technical processes, and prepare progress reports.
• Provide technical support and oversight to less-experienced team members.
• Assist with regulatory support, Data Sharing Agreements, and other project documentation.
• Collaborate with the Principal Investigator, Co-Investigators, and research team in conducting the study.
• Contribute to drafting and submitting abstracts, manuscripts, and reports for dissemination.
• Prepare research progress reports as required.
• Analyze data and write up results.
• Present complex information effectively to a range of audiences.
• Provide data management assistance.
• Provide project close-out support.
• Support protocol adherence, enrollment targets when applicable, monitoring visits, and regulatory and administrative details.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree