Digital Health And Behavior Data Scientist

This position will provide advanced computational and data science expertise to support digital health and behavioral research within the NIH Intramural Research Program. This position is responsible for leading multimodal data integration, machine learning and simulation modeling, and supporting human subjects research activities to advance understanding of substance use, treatment outcomes, and recovery. The ideal candidate will demonstrate a strong publication record, including peer-reviewed scientific papers as first author, senior author, or contributing middle author, reflecting substantive contributions to computational modeling, machine learning, AI-driven research, or digital health studies.

• Good Clinical Practice (GCP)

• Computer Science
• Social Psychology
• Information Sciences
• Statistics and Decision Science

• SQL
• Pytorch
• TensorFlow
• Hugging Face
• Pandas
• Open AI API Integration
• AWS, Azure
• GitHub, Jupyter Notebook
• RedCap
• Mobile Sensing Platforms
• Python
• MATLAB
• Linux
• R Skills
• Machine Learning Generative AI
• Natural Language Processing / LLMs
• Computational Simulation Modeling
• Multimodal Time-Series Data Analysis
• Reproducible Data Science (Python/R)
• Human Subjects Research Support
• Manuscript writing
• Ordering Supplies
• Data Presentation
• Data Analysis
• SOP writing

• Run Validation - Ad-Hoc
• Meet with lab members to present updates - Ad-Hoc
• Documented Data Pipelines: Fully documented and reproducible data ingestion, preprocessing, quality control, and feature extraction pipelines for all assigned multimodal datasets. - Ad-Hoc
• Curated Analytical Datasets: Cleaned, integrated, and analysis-ready datasets with accompanying data dictionaries and processing documentation. - Ad-Hoc
• Validated Models: Implemented and evaluated machine learning, NLP, and/or generative AI models with documented methodology, performance metrics, validation results, and interpretation of findings. - Ad-Hoc
• Simulation Models: Developed computational simulation models (e.g., agent-based, predictive, or generative agent models) with written documentation of assumptions, parameterization, calibration, and sensitivity analyses. - Ad-Hoc
• Reproducible Code Repositories: Version-controlled, well-documented code repositories (with clear README files) sufficient for replication by other researchers. - Ad-Hoc
• Technical Documentation: Written model documentation describing design decisions, input features, target definitions, modeling tradeoffs, and limitations. - Ad-Hoc
• Progress Summaries: Written summaries of completed analyses, model performance, dataset updates, and next steps. - Ad-Hoc
• Manuscript Drafts and Figures: Draft and revised scientific manuscripts, methods and results sections, tables, and figures suitable for peer-reviewed publication. - Ad-Hoc
• Presentations: Slide decks and presentation materials for internal reviews, lab meetings, and scientific conferences. - Ad-Hoc
• Human Subjects Research Support Documentation: Completed consent documentation support, data collection tracking logs, and documentation of participant-facing digital data procedures. - Ad-Hoc

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  Develop and implement computational, statistical, and simulation-based experimental designs to evaluate behavioral and digital health research hypotheses. - 1
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  Oversee project data quality; analyze and interpret project data. - 2
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  Write technical reports and prepare manuscripts. - 3
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  Develop and share analytical tools, scripts, and reproducible workflows to support laboratory research activities. - 4
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  Review scientific data to determine if a research program can be developed around an idea or data package. - 5
• →Supports the planning and execution of research experiments in the context of the laboratory's overall research program.
• →Design and conduct experiments and studies requiring the application of a broad professional knowledge of scientific theories and principles.
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  Advance the science through proposing and investigating new target projects for initiation based on novelty and relevance to human health.

• →Supports laboratory staff on research projects and techniques.
• →Work with staff on the interpretation of experiments performed by research scientists.
• →Independently direct and conduct special research projects that have a high priority for the laboratory with special emphasis in the development of novel research treatments.
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  Work with postdoc/biological scientists to perform statistical analysis for research projects.

• →Provide technical guidance to laboratory staff on computational modeling, machine learning methods, and data analysis strategies.
• →Maintains laboratory equipment and the training of others in their use.
• →Operate, troubleshoot and train others to use laboratory equipment and software.
• →Provide advice and assistance to users in designing experiments, using instrumentation, data acquisition and analysis, and preparing figures for publication.
• →Assists in maintaining adequate space and facilities for ongoing and projected research studies.
• →Participate in the laboratory’s review of future proposals for resource allocations.
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  Evaluates, analyzes and interprets research data, communicates results and methods in reports, presentations, and manuscripts.

• →Conduct bioinformatics data analyses and statistical analyses; prepare data for abstracts and manuscripts.
• →Maintain a detailed and up-to-date electronic laboratory notebook detailing all experiments.
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  Collaborate with investigators to translate research questions into quantitative modeling and data-driven study designs.