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The U.S. government is closed. This site will not be updated; however, NOAA websites and social media channels necessary to protect lives and property will be maintained. To learn more, visit commerce.gov. 

For the latest forecasts and critical weather information, visit weather.gov.

Marine Mammal Stock Assessment Program Support (Virtual or Silver Spring, MD)

Summary / Description

Assessing marine mammal stocks gives us valuable information on population trends, productivity rates, estimates of human-caused mortality and other sources of serious injury, and more. These assessments allow us to evaluate the effectiveness of conservation and recovery measures, and to adjust management approaches as needed. The National Marine Fisheries Service (NMFS) is actively transitioning to a reproducible workflow for marine mammal Stock Assessment Reports (SARs) by utilizing Quarto and GitHub to automate documentation and enhance scientific transparency and efficiency. We are transitioning to a standardized process to move away from manual reporting toward “code-to-document” automation, allowing NMFS to use Quarto to combine narrative text with code. This is currently being piloted by Alaska Fisheries Science Center and Pacific Islands FIsheries Science Center, with the potential goal of all marine mammal SARs transitioning to the reproducible process. 

This internship will take place with NMFS Office of Protected Resources (OPR) and Office of Science and Technology (OST), who are responsible for coordinating review and publishing final SARs. The intern selected for this project would help identify what key output data we may need to easily query from the SARs, and develop a proof of concept for how these data would be used and queried across all the different regional SAR repositories. This project would support NMFS’ policies and goals of transparency, open science, and increase efficiency in producing marine mammal SARs.

Skills Required

  • We are seeking an upper-level undergraduate (or graduate) student with an interest in environmental, marine mammal, or oceanographic data management and a quantitative skillset and coding background. 
  • At a minimum, the student should have intermediate level experience using R to manipulate and aggregate data. Preference will be given to a student with additional experience with R Markdown, GitHub, Quarto, R Shiny, or database development. 
  • The student should be self-motivated, organized, and have excellent attention to detail.

Type of Opportunity

  • Research and Data Analysis

Location

  • Virtual (preferred) or Silver Spring, MD (housing assistance is not available). If virtual, a personal computer and a Gmail account for use of google suite, and ability to download and access software needed under skills required section are required. 

Other Information

  • Intern Supervisor:  Meghan Gahm and Eric Patterson
  • Number of Slots Available:  1