PREP0002593 PREP Machine Learning Associate

PREP Research Associate

Opportunity No.: PREP0002593

This position is part of the National Institute of Standards and Technology (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, and 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.

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PREP Machine Learning Associate

Project Description:

The goal of this project is to reduce firefighter deaths and injuries due to flashovers and to enhance firefighting safety and situational awareness in commercial building environments.

Flashover is an extreme fire event. When it occurs, there is a near-simultaneous ignition of most of the directly exposed combustible materials within a compartment. Due to the large heat release rate, gas temperatures increase rapidly and may exceed 800 °C. Rapid fire progression, such as flashover, is the number two cause of firefighter deaths and injuries. Over the past 10 years, approximately 700 firefighters were killed and more than 200,000 were injured. Unfortunately, there are still no tools that firefighters can use to detect flashovers, so they rely on their past experience using so-called flashover indicators that are difficult to recognize. For these reasons, researchers at NIST have been developing data-driven models that can be used to help firefighters predict the potential of flashovers.

Existing modeling approaches cannot be used in real-time firefighting due to two major problems. The first problem is that the existing models are numerically inefficient for real-time applications. Even when high-performance computing is being used, a single calculation takes more than 5 minutes. The second problem is that the fire scenarios being considered by these models are oversimplified. Sensors are assumed to work at extremely high temperatures and the fire locations and vent opening conditions are assumed to be well known. In real-life situations, however, sensors will fail and the inside conditions are never known. NIST has established a smart firefighting project to enhance firefighting safety and situational awareness by enabling real-time prediction of flashover conditions in commercial building environments. To reach this goal, the relationships of fire data, such as temperature, smoke, and species concentrations, and the effect of data quality, must be understood to use machine learning for effective real-time predictions.

Key Responsibilities will include but are not limited to:

• Enhance the existing machine learning-based flashover prediction model
• Play an active role in developing a functional platform to process data streams in real-time
• Work with NIST research staff for machine learning model deployment in full-scale testing

Desired Qualifications:

• Bachelors, masters, PhD., or equivalent experience in computer science, engineering, or related fields
• Experience in Python
• Knowledge of other programming languages, such as Javascript and MATLAB, is a plus
• Basic working knowledge of Tensorflow and/or Pytorch
• Ability to identify, manage, and overcome technical hurdles for machine learning model deployment

Other Details:

• Full-time: the participant is expected to work 40 hours a week, or
• Part-time: the participant is expected to work 16-20 hours a week
• Location: the participant will work at the NIST Gaithersburg Campus.
• Duration: this is expected to be a six-month to one-year position. Extensions are sometimes granted depending on the availability of funds.
• For questions related to the research project or the nature of the work in this position, please contact Dr. Andy Tam (waicheong.tam@nist.gov). For questions related to the online application or NIST PREP more generally, please contact Dr. John Brandau (john.brandau@morgan.edu).

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.

PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate the administrative functions of the PREP Program.

Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.

Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use the information you submit for the purpose stated.