Postdoctoral Fellow (PREP0004125)

Johns Hopkins University; Baltimore (MD); On-site; USD 70,000 - 90,000; Full time

Benefits offered by this job

Health benefits

Retirement support

Career development

Job summary

Johns Hopkins University is seeking a PREP Research Associate to join the National Institute of Standards (NIST) program. This role focuses on acquiring fire data and developing prediction models that aim to enhance firefighting safety. Candidates should have a Ph.D. in relevant fields and a solid background in Fire Safety Engineering.

Proficiency in CFAST, Python, and other tools is essential. The compensation package includes benefits that promote health, life, and career development. Equal opportunity commitment ensures a diverse workplace.

Qualifications

• Ph.D. in Architecture, Civil Engineering, or similar field.
• Solid background in Fire Safety/Protection Engineering.
• Proficiency in CData, CFAST, FDS, Python, MATLAB, and R.

Responsibilities

• Acquire fire data from realistic fire scenarios in commercial buildings using CFAST Data Generation.
• Develop a prediction model correlating flashover conditions to temperature behaviors.
• Collaborate with the existing fire research community and participate in meetings and presentations.

Skills

Fire Safety/Protection Engineering

Python

MATLAB

R

CData

CFAST

Numerical Model Development

Education

Ph.D. in relevant field

Tools

CFAST

FDS

Job description

PREP Research Associate

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. Employees in this position will perform technical work that underpins the scientific research of the collaboration.

Project Description

The goal of this project is to reduce firefighter deaths and injuries due to flashover and to enhance firefighting safety and situational awareness in commercial building environments. The work will involve acquiring fire data, developing a numerically efficient prediction model for flashover conditions, and collaborating with the fire research community to translate findings to stakeholders.

Key Responsibilities

• Acquire fire data, including gas temperatures, smoke concentrations, and gas species concentrations, from realistic fire scenarios in commercial building environments using CFAST Data Generation (CData). Lead the collection of data and study of data behavior.
• Develop an accurate and numerically efficient prediction model that correlates flashover conditions to temperature behaviors, generalizing across building structures without prior knowledge of layout or interior conditions. Lead the optimization of the model.
• Collaborate and coordinate research with the existing fire research community, assist in developing research plans, and participate in meetings, presentations, and report preparation to support data‑driven modeling for enhancing firefighting safety.

Qualifications

• US citizen preferred.
• Ph.D. in Architecture, Civil Engineering, Safety Science and Engineering, Safety Engineering, Fire Protection Engineering, or a similar field.
• Solid background in Fire Safety/Protection Engineering.
• Proficiency in CData, CFAST, and FDS.
• Proficiency in Python, MATLAB, and R.
• Well‑established publication record in Q1 SCI journals.
• Practical research experience in building recommendation systems and use of computer clusters.

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. The actual compensation offered may vary depending on factors such as location, skills, experience, and other circumstances.

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. 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. Qualified individuals are given access to all academic and employment programs, benefits, and activities on the basis of demonstrated ability, performance, and merit.

EEO is the Law

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