Postdoctoral Fellow (PREP0005175)

Johns Hopkins University; Baltimore (MD); On-site; USD 70,000 - 110,000; Full time

Job summary

Johns Hopkins University is seeking a PREP Research Associate to advance decision science and computational methods for community resilience. You will standardize and analyze heterogeneous data, develop reproducible workflows, and apply ML/NLP to extract actionable insights from field data and transcripts.

The role emphasizes collaboration with NIST researchers and external partners, with responsibility for software prototyping, documentation, and dissemination of results.

Qualifications

• PhD or ABD in computational science or related field.
• 3+ years applying computational methods to heterogeneous data.
• Experience with multimodal sensing or time-series data.
• Experience with ML/statistical methods for data fusion/classification.
• Familiarity with NLP or language-model techniques is desirable.
• Proficiency in programming and reproducible research practices.
• Strong communication in interdisciplinary teams.

Responsibilities

• Develop and evaluate schemas, metadata, vocabularies, and data dictionaries for multimodal field data.
• Design reproducible workflows to ingest, clean, synchronize, and link data sources.
• Support field-data collection activities using mobile sensing and infrastructure monitoring.
• Develop ML/NLP methods to classify observations and extract relations.
• Create research software, communicate findings, and document datasets and code.

Skills

Multimodal data analysis

NLP methods

Statistical modeling

Programming & reproducible research

Scientific communication

Education

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

Tools

Python

R

Git

Jupyter

Job 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. Data may include mobile or fixed sensor measurements, time-series data, accelerometer and gyroscope measurements, GPS or other geospatial information, infrastructure observations, surveys, interviews, and other qualitative records. The associate will also investigate machine-learning and natural-language-processing methods for extracting entities, relationships, and causal information from field and interview data and linking those representations with quantitative measurements. The research will contribute to field-data collection strategies, interoperable data products, analytical prototypes, technical documentation, reports, and presentations for NIST researchers and external collaborators.

Key responsibilities will include but are not limited to:

• 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 relation 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

U.S. Citizens are Preferred

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. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristics. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors or demographic characteristics that are irrelevant to the program involved.

Pre-Employment Information

If you are interested in applying for employment with Johns Hopkins University and require special assistance or accommodation during any part of the pre-employment process, please contact the HR Business Services Office at [e-mail]. For TTY users, call via Maryland Relay or dial 711. For more information about workplace accommodations at Johns Hopkins University for disabilities, medical conditions (including medical conditions related to pregnancy or childbirth), accessibility, or religious reasons, please visit accessibility.jhu.edu.

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. When deciding whether a candidate's conviction history is job-disqualifying, the University considers the nature and gravity of the offense, the time that has passed since the conviction, and the nature of the job being sought.

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. This change does not apply to the School of Medicine (SOM). SOM hires must be fully vaccinated with an FDA COVID-19 vaccination and provide proof of vaccination status. We still require all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the seasonal flu vaccine or COVID-19 vaccine (for SOM) requirement(s) may be provided to individuals with sincerely held religious beliefs or medical conditions that preclude them from receiving the vaccine. Requests for an exception must be submitted to the JHU vaccination registry. For additional information, applicants for SOM positions should visit https://www.hopkinsmedicine.org/coronavirus/covid-19-vaccine/ and all other JHU applicants should visit https://covidinfo.jhu.edu/health-safety/covid-vaccination-information/.

The following additional vaccine requirements may apply, depending upon your campus.

The pre-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those candidates who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.