Postdoctoral Fellow — Data Science for Community Resilience

Johns Hopkins University; Gaithersburg (MD); On-site; USD 75,000 - 85,000; Full time

Job summary

Johns Hopkins University in Baltimore is seeking a PREP Research Associate to support NIST Community Resilience research. The role focuses on creating standardized data structures, metadata, and reproducible workflows for multimodal field data, including sensor and geospatial information.

The associate will also explore machine-learning and NLP methods to extract entities and causal relations from transcripts, linking outputs to structured datasets and contributing to publications and technical

Qualifications

• PhD degree, or current PhD candidacy with all degree requirements completed except the dissertation in Computational Science, Data Science, Computer Science, Engineering, Applied Mathematics, Systems and Control, or related field.
• Three+ years of relevant research applying computational methods to heterogeneous data.
• Experience with multimodal sensing or time-series data (accelerometer, gyroscope, GPS) for infrastructure or transportation monitoring.
• Experience with ML or statistical methods for classification, inference, data fusion, or pattern discovery across heterogeneous data.
• Experience with NLP or language-model-based methods for information extraction from transcripts or interviews.
• Proficiency with programming and scripting tools, version control, and reproducible research practices.
• Strong communication skills in interdisciplinary research collaboration and publications.

Responsibilities

• Develop and evaluate standardized schemas, metadata elements, data dictionaries, and quality-control rules for multimodal field data.
• Design reproducible workflows to ingest, clean, validate, synchronize, and link heterogeneous data sources.
• Support field-data collection activities using sensor measurements and mobile sensing.
• Develop ML and NLP methods to classify observations and extract entities and relationships.
• Develop research software and documentation; ensure datasets and code are reproducible and archived.

Skills

Multimodal sensing

Time-series data

Machine-learning

Natural-language processing

Programming

Version control

Reproducible research

Documentation

Collaborative workflows

Interdisciplinary communication

Education

PhD or ABD in Computational Science/Data Science/CS/Engineering

Job description

Johns Hopkins University in Baltimore is seeking a PREP Research Associate to support NIST Community Resilience research. The role focuses on creating standardized data structures, metadata, and reproducible workflows for multimodal field data, including sensor and geospatial information.

The associate will also explore machine-learning and NLP methods to extract entities and causal relations from transcripts, linking outputs to structured datasets and contributing to publications and technical