Postdoctoral Fellow (Data Engineering & AI/ML)
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Before you apply
Salary$65k – $79k
LocationBethesda, MD
Work modeon-site
Typefull-time
SeniorityMid
Experience5+ yrs
Company size201–500 people
PostedNov 2, 2026 · 3d ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
PhD required
MD required
5+ years experience with multimodal data analysis
Proven experience with signal processing (e.g., time-series biosensor data)
Hands-on experience with version control systems (e.g., Git) and ability to work in a collaborative coding environment
Experience and/or a strong desire to learn the ins and outs of cloud computing, including managing cloud-native data warehouses and standing up ETL pipelines
Ability to work in a fast-paced, multidisciplinary, multi-site (sometimes asynchronous) team environment
Demonstrate competence in oral and written communication
Must be organized, attentive to detail, and possess a positive, friendly and professional demeanor
Ability to be flexible with changing priorities and available to interact with employees, clients and sponsors of all levels
Ability to exercise independent judgment in fast-paced, high-pressured environment with strict deadlines and to manage multiple projects
Computer skills including at least intermediate level experience with Excel and other Microsoft Office Software
1-2 years medical research project management experience strongly desired, preferably with 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 system
Skills
Git
Excel
Microsoft Office
signal processing
cloud computing
ETL
machine learning
model development
model tuning
deploying models
data warehouses
cloud-native data warehouses
version control systems
About the role
About the Position
The Post-Doctoral Fellow I provides assistance to the Principal Investigator, Co Investigators, and Research Staff. S/he ensures enrollment numbers are successfully met, when applicable, and protocol adherence, monitoring visits, overseeing regulatory and administrative details, data management assistance and project close-out support is provided.
About the Project
This project is a multi-institution research collaboration with Stanford, Johns Hopkins, the Veteran Affairs (VA), and the Department of War (DoW) to build a sleep foundation model. Unlike traditional AI models, a sleep foundation model relies on self-supervised learning on vast amounts of physiological sleep study data (petabyte-level). By generating representations (embeddings) from the sleep data, the team aims to forecast future health risks and uncover latent patterns that traditional sleep scoring metrics miss.
Salary Range
$65,000 - $79,000. Salaries are determined based on several factors including external market data, internal equity, and the candidate’s related knowledge, skills, and abilities for the position.
Qualifications
•
PhD or MD required
•
1-2 years medical research project management experience strongly desired, preferably with Department of Defense
•
5+ years experience with multimodal data analysis
•
Proven experience with signal processing (eg, time-series biosensor data)
•
Hands-on experience with version control systems (eg, Git) and ability to work in a collaborative coding environment
•
Experience and/or a strong desire to learn the ins and outs of cloud computing, including managing cloud-native data warehouses and standing up ETL pipelines
Nice to have
•
Preferred qualifications: strong knowledge of sleep science, familiarity with machine learning workflows including model development, model tuning, and deploying models at scale
•
Ability to work in a fast-paced, multidisciplinary, multi-site (sometimes asynchronous) team environment
•
Knowledge of military system, preferred.
•
Demonstrate competence in oral and written communication
•
Must be organized, attentive to detail, and possess a positive, friendly and professional demeanor
•
Ability to be flexible with changing priorities and available to interact with employees, clients and sponsors of all levels
•
Ability to exercise independent judgment in fast-paced, high-pressured environment with strict deadlines and to manage multiple projects
•
Computer skills including at least intermediate level experience with Excel and other Microsoft Office Software
Responsibilities
•
Design, develop, and deploy scalable applications (both front-end interfaces and back-end data pipelines) to support large-scale research
•
Build ETL pipelines that ingest multimodal datasets (wearables, cross-referenced with EHRs, PSGs, and subjective sleep metrics), ensuring efficient storage, retrieval, and processing of massive datasets (+1million records)
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Support the build-out of scalable infrastructure to support advanced machine learning models using physiological features and sleep microarchitectures
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Optimize application performance and scalability through performance tuning, code refactoring, and database optimization techniques
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Stay updated with emerging industry trends, academic literature, and technologies in data engineering, cloud architecture, and machine learning to continuously improve the lab’s technical capabilities
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Ensure data integrity throughout engineering workflows. Assist in the preparation of Standard Operating Procedures (SOPs), analytical frameworks, and technical documentation
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Maintain open communication with leadership, advise on technical processes, and curate progress reports
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Provide technical support and oversight to team members with less experience
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Assist in regulatory support, Data Sharing Agreements, and other project documentation
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Collaborate and assist the Principle Investigator, Co-Investigators and research team in the performance the research study
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Contribute to the drafting and submitting of abstracts, manuscripts and reports for dissemination
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Prepare progress reports on research as required
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Analyze and write-up data
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Present complex information effectively to a range of audiences
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Provide data management assistance
•
Provide project close-out suppo