Postdoctoral Fellow in Decision Science and Computational Methods for Community Resilience

1000scholars; Baltimore (MD); On-site; USD 65,000 - 90,000; Full time

Job summary

Johns Hopkins University seeks a PREP Research Associate to support the NIST PREP program focused on Decision Science and Computational Methods for Community Resilience. You will help standardize and analyze heterogeneous field data, create data schemas, and develop reproducible workflows for multimodal sensing and time-series integration.

The role requires programming proficiency, experience with ML/NLP methods, and strong communication to collaborate with NIST researchers and external

Qualifications

• PhD or ABD in Computational Science, Data Science, Computer Science, Engineering, Applied Mathematics, Systems and Control, or a closely related field.
• Three or more years of relevant research or professional experience applying computational methods to heterogeneous scientific, engineering, infrastructure, transportation, or field-collected data.
• Demonstrated experience with multimodal sensing or time-series data, preferably including accelerometer, gyroscope, GPS/geospatial, acoustic, smartphone, or related field measurements used for infrastructure or transportation monitoring.
• Experience developing machine-learning or statistical methods for classification, inference, data fusion, or pattern discovery across heterogeneous data sources, together with the ability to prototype reproducible data-processing and analysis workflows.
• Experience with natural-language processing or language-model-based methods for entity and relationship classification, information extraction, causal-model extraction, or analysis of interviews, transcripts, or other unstructured text is highly desirable.
• Proficiency with programming and scripting tools used in computational research, along with familiarity with version control, reproducible research practices, structured documentation, and collaborative software or data workflows.
• Strong oral and written communication skills demonstrated through interdisciplinary research collaboration, technical presentations, publications, workshops, or mentoring, and the ability to work effectively with NIST researchers and external stakeholders.

Responsibilities

• The associate will support NIST Community Resilience research by developing methods to standardize, integrate, and analyze heterogeneous field data used to characterize infrastructure, community conditions, and resilience outcomes.
• Develop and evaluate standardized schemas, metadata elements, controlled vocabularies, data dictionaries, provenance records, and quality-control rules for multimodal community resilience field data.
• Design reproducible workflows to ingest, clean, validate, synchronize, link, transform, and version heterogeneous data sources, including time-series sensing and location data.
• Support design and analysis of field-data collection activities, including mobile sensing and infrastructure monitoring using signals such as acceleration, location, sound, and related environmental data.
• Develop and test statistical, machine-learning, and NLP methods to classify observations and extract entities, relationships, and causal structures from unstructured records, linking outputs to structured datasets.
• Develop research software or analytical prototypes, communicate findings in internal and stakeholder meetings and technical publications, and ensure datasets, code, and documentation are reproducible and archived.

Education

PhD or ABD

Tools

Version control

Job description

General Description

PREP Research Associate

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.

Research Title: Decision Science and Computational Methods for Community Resilience

The work will entail:

• The associate will support NIST Community Resilience research by developing methods to standardize, integrate, and analyze heterogeneous field data used to characterize infrastructure, community conditions, and resilience outcomes. The work will focus on creating consistent data structures, metadata, data dictionaries, quality-control procedures, and reproducible computational workflows that allow data collected across field studies, communities, and time periods to be compared and combined...
• Develop and evaluate standardized schemas, metadata elements, controlled vocabularies, data dictionaries, provenance records, and quality-control rules for multimodal community resilience field data, including sensor, geospatial, infrastructure, survey, and interview data.
• Design reproducible workflows to ingest, clean, validate, synchronize, link, transform, and version heterogeneous data sources, with particular attention to integrating time-series sensing and location data with contextual or qualitative information.
• Support the design and analysis of field-data collection activities, including mobile or smartphone-based sensing and infrastructure monitoring using measurements such as acceleration, angular motion, location, sound, or related environmental and operational signals.
• Develop and test statistical, machine-learning, and natural-language-processing methods to classify observations and extract entities, relationships, and causal structures from unstructured records such as interviews or transcripts, and connect these outputs to structured field datasets.
• Develop research software or analytical prototypes, communicate findings in internal and stakeholder meetings and technical publications, and ensure that datasets, code, protocols, model outputs, and documentation are reproducible and archived for use by the larger NIST research program.

Qualifications

• A PhD degree, or current PhD candidacy with all degree requirements completed except the dissertation (all-but-dissertation/ABD), in Computational Science, Data Science, Computer Science, Engineering, Applied Mathematics, Systems and Control, or a closely related field.
• Three or more years of relevant research or professional experience applying computational methods to heterogeneous scientific, engineering, infrastructure, transportation, or field-collected data.
• Demonstrated experience with multimodal sensing or time-series data, preferably including accelerometer, gyroscope, GPS/geospatial, acoustic, smartphone, or related field measurements used for infrastructure or transportation monitoring.
• Experience developing machine-learning or statistical methods for classification, inference, data fusion, or pattern discovery across heterogeneous data sources, together with the ability to prototype reproducible data-processing and analysis workflows.
• Experience with natural-language processing or language-model-based methods for entity and relationship classification, information extraction, causal-model extraction, or analysis of interviews, transcripts, or other unstructured text is highly desirable.
• Proficiency with programming and scripting tools used in computational research, along with familiarity with version control, reproducible research practices, structured documentation, and collaborative software or data workflows.
• Strong oral and written communication skills demonstrated through interdisciplinary research collaboration, technical presentations, publications, workshops, or mentoring, and the ability to work effectively with NIST researchers and external stakeholders.

U.S. Citizens are Preferred

Privacy Act Statement

Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)

Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty...

Salary Range

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

Total Rewards

Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/.

Equal Opportunity Employer

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students...

Background Checks

After receiving a conditional offer, the successful candidate(s) for this position will be subject to a pre-employment background check including education verification...

EEO is the Law

https://www.eeoc.gov/employees-job-applicants

Vaccine Requirements

Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine… Other vaccine requirements may apply, depending upon your campus. Please contact the hiring department for more information.