TRANSPORTATION RESILIENCE PLANNING INTERN Job at METROPOLITAN WASHINGTON COUNCIL OF GOVERNMENTS, Washington DC

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  • METROPOLITAN WASHINGTON COUNCIL OF GOVERNMENTS
  • Washington DC

Job Description

Job Description

Job Description

OVERVIEW

The Metropolitan Washington Council of Governments (COG) is seeking an intern to support the Transportation Resilience Planning Program in the Department of Transportation Planning. The employment period is expected to begin in January 2026 and end in June 2026 with the possible opportunity to extend.

The Department of Transportation Planning supports the National Capital Region Transportation Planning Board (TPB), the federally designated metropolitan planning organization (MPO) for the Washington, D.C. region. The TPB plays an important role as the regional forum for transportation planning in the National Capital Region. It prepares plans and programs that the federal government must approve in order for federal-aid transportation funds to flow to the Washington region.

Planning for and adapting to the impacts of extreme weather and natural hazards is critical to ensure the region’s transportation system can operate efficiently and safely. The TPB’s regional resilience planning activities consider vulnerability, risks, and proactive anticipation of natural hazards to maintain service operations and ensure the health and safety of travelers. The TPB collaborates with its member agencies on decision-making for the transportation network and shares resources to help regional stakeholders progress towards increasing transportation resilience in the National Capital Region.

POSITION SPECIFICATIONS

The successful candidate will mainly support a resilience research project focused on better understanding and mapping the impacts of extreme weather on the regional transportation system, with the opportunity to also provide assistance in a variety of Transportation Resilience Planning Program activities, including supporting the regional transportation resilience subcommittee, coordinating resilience related efforts across local jurisdictions and transit agencies in the region, and supporting other long range planning regional plans and projects with transportation resilience touchpoints.

Work activities may include:

  • Collect, process, and analyze historical rainfall and extreme weather data.
  • Integrate datasets with transportation network and closure point data.
  • Conduct spatial analysis and mapping using GIS tools.
  • Apply statistical or machine learning methods (potentially including large language models) to identify patterns in event data.
  • Draft written summaries, figures, and maps to communicate findings to planners and stakeholders.
  • Support other resilience and long-range transportation planning tasks as needed, including but not limited to: attend internal and external meetings with consultant teams and local jurisdictions/agencies, review documents, brainstorm research/study ideas, research state of practice, etc.


The successful candidate should possess the following skills:

  • Current graduate student or recent graduate in urban planning, transportation, geography, environmental science, data science, or a related field.
  • Strong interest in climate resilience, transportation planning, and/or long-range planning.
  • Experience with data analysis (Python, R, or similar), preferred but not required.
  • Proficiency in GIS mapping (ArcGIS, QGIS, or similar), preferred but not required.
  • Familiarity with or interest in large language models (LLMs) for data processing and analysis, preferred, but not required.
  • Strong written and verbal communication skills.
  • Ability to work independently and collaboratively.

EDUCATION AND EXPERIENCE

Applicant should be a current student or recent graduate in urban planning, transportation, geography, environmental science, data science, or a related field. Graduate level preferred.

HOURS AND EMPLOYMENT PERIOD

15-28 hours per week

The position is expected to begin in January 2026 and end in June 2026.

Job Tags

Local area,

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