Senior Researcher (PREP0003005)

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.

 

Goals and Approach:

 

The PREP researcher will focus time on efforts that support the project: “Cost-Effective Resource Allocation Strategies for Community Resilience.” (Applied Economics Office, Dr. Jennifer Helgeson).

 

It is expected that the PREP Researcher will engage in all steps of the research process, including but not limited to: literature review, data collection, data analysis, preparation of reports and archival journal articles, as well as reporting and communication with stakeholders. 

 

The objective of this role is to support community resilience planning through the development of methods and tools that evaluate the economic impacts of disruptive events and persistent stressors, while accounting for stakeholder perceptions and associated decisions related to future event uncertainty and co-benefit (co-cost) valuation. There will be special focus on criteria and methods to improve the resilient performance of structural systems in the built environment while maintaining cost-effectiveness and supporting community-defined objectives in addition to resilience.

 

The goal is to create a method to summarize various aspects of text (e.g. public comments on proposed federal action) to typify public concern. We will use potential climate change policies (mitigation/adaptation) and fisheries data. We will also be developing a framework so that its useful as a tool to inform decision-makers. It will not facilitate decision-making but provide new information for decision-makers. The method is value-neutral and domain generic and about metrics of public comment.

 

Proof of concept: We hope to use scientific literature to create concept maps, and public comment to typify different ways of reasoning and compare model graphs/structures to understand differences. The goal is to summarize large datasets and give nuance to it (cause and effect relationships, sentiment and feeling) and dominant cause and relationships to better understand public perception. We plan to visualize this.

 

Key responsibilities will include but are not limited to:

 

Collaborate on data and methods to improve the methodology for measuring economic impact of community resilience planning, which is organized around the performance metric of ‘cost plus loss’ minimization – i.e., the economically optimal level of investment in prevention and mitigation activities to reduce future disturbance and disaster-related losses, as well as related expenditures that minimize the combined investment cost plus the value of expected losses. 

 

Objectives

a. To develop a framework for using NLP to analyze policy documents, public comments, and social media posts at the intersection of community resilience and climate change.

b. To identify key conceptions, preferences, and stakeholder-perceived alternatives in (a) public comments and (b) social media data.

c. To quantify and understand uncertainty in the use of NLP and to provide verification and validation for the developed methods.

d. To develop replicable methods that complement existing community resilience economics methods for integrating, quantifying , curating, and communicating public comment features identified in 2.

e. To evaluate how public comments influence the development and modification of climate adaptation and mitigation policies, as well as community resilience policies and preferences.

Qualifications

§  Graduate degree in Computer Science, Economics, Social Science, Policy, Environmental Science