Organization: National Oceanic and Atmospheric Administration (NOAA)
Reference Code: NOAA-NCCOS-2023-05
How to Apply
Connect with ORISE…on the GO! Download the new ORISE GO mobile app in the Apple App Store or Google Play Store to help you stay engaged, connected, and informed during your ORISE experience and beyond!
A complete application package consists of:
- An application
- Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal institution systems may be submitted. Click Here for detailed information about acceptable transcripts.
- A current resume/CV
- Two educational or professional recommendations
All documents must be in English or include an official English translation.
Application Deadline: 6/9/2023 3:00:00 PM Eastern Time Zone
Description
*Applications will be reviewed on a rolling-basis.
NOAA Office/Lab and Location: A research opportunity is currently available with the National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Stressor Detection and Impacts Division (SDI), Harmful Algal Bloom (HAB) Forecasting Branch. The HAB-F Branch delivers near real-time forecasting products for predicting the intensity/severity, location, and the potential health risk HABs pose in the Great Lakes and coastal regions of the U.S. While national in scope, forecasting efforts and products address regional needs and specific HAB species. The product sets are intended to support coastal resource managers, public health officials, researchers, and the public. The appointment will be based at the University of California, San Diego.
The National Oceanic and Atmospheric Administration (NOAA) formed the National Centers for Coastal Ocean Science (NCCOS) in 1999 as the focal point for NOAA’s coastal ocean science efforts. NCCOS uses cutting-edge research and high-tech instrumentation to provide citizens, coastal managers, public health officials, and other decision makers with reliable information needed to determine how best to protect environmental resources and public health, preserve valued habitats, and improve the way communities interact with coastal ecosystems. The NCCOS is headquartered in Silver Spring, MD but also has research labs across the nation. The NCCOS also has many assets including research programs, vessels, satellites, science centers, laboratories, and a vast pool of distinguished scientists and experts.
Research Project: Under the guidance of a technical mentor, the selected candidate will gain experience in various research activities including digital microscopy, machine learning, and artificial intelligence for the detection and enumeration of harmful algal bloom (HAB) forming species. The candidate will also gain experience in the development of a graphical interface/digital platform to display the digital microscopy ML/AI outputs and gain experience in data analytics.
Specific objectives include algorithm development for digital microscopy images of multiple HAB forming species across the US, mainly targeted at species common to the Florida coast and Chesapeake Bay.
1) Numerous potentially toxic phytoplankton are known to bloom in the Chesapeake Bay and pose a threat to shellfish, fish, public health and the ecology. In an effort to better protect fisheries and farmed shellfish in the Chesapeake Bay, early identification of potentially harmful algal blooms (HABs) is critical. The diversity of HAB species and their unique impacts on fisheries, aquaculture, recreation, and/or drinking water, necessitates the development of rapid detection technologies to provide early warning in the region. The candidate will conduct research on developing AI/ML strategies to detect these HAB species in mixtures, initially based on calibration with laboratory cultures and eventually moving to field validation efforts.
2) In the Gulf of Mexico Karenia brevis forms extensive red tide events that cause major respiratory issues along the Gulf Coast of Florida. The fellow will conduct research to develop AI/ML detection strategies for Karenia brevis, first using laboratory cultures and then moving into field validation. This microscope/camera technology will then be rolled into the HABscope volunteer network and incorporated into the NCCOS Respiratory Irritation Forecast. In an effort to train the instrument for new HAB species, the selected fellow should have experience in AI/ML technology for image analysis. The fellow will assist in developing new algorithms and calibrating the instrument for new phytoplankton species. This will also require documenting the methods used and modifying existing training manuals to include these new capabilities.
Learning Objectives:
- Develop an understanding of phytoplankton species common in the Chesapeake Bay and Florida
- Learn about HAB-F capabilities in monitoring and modeling, including use of satellite data products and models
- Expand familiarity with statistical and coding software such as R, Python and/or Matlab
- Develop skills in using AI technology for identifying phytoplankton types and the use of the HABscope for phytoplankton enumeration
- Develop skills in information dissemination on web/app portals and developing training material
Mentor: The mentor for this opportunity is Kaytee Pokrzywinski (kaytee.pokrzywinski@noaa.gov). If you have questions about the nature of the research please contact the mentor.
Anticipated Appointment Start Date: June 2023. Start date is flexible and will depend on a variety of factors.
Appointment Length: The appointment will initially be for four months (June through September) but may be renewed upon recommendation of NOAA and is contingent on the availability of funds.
Level of Participation: The appointment is full-time.
Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience.
Citizenship Requirements: This opportunity is available to U.S. citizens.
ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and NOAA. Participants do not become employees of NOAA, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE.
Questions: If you have questions about the application process please email NOAA@orau.org and include the reference code for this opportunity.
Qualifications
The qualified candidate should have received a master’s or doctoral degree in one of the relevant fields or be currently pursuing one of the degrees with completion before May 31, 2025. Degree must have been received within the past two years.
Preferred skills:
- Research experience, a demonstrated ability to work independently and part of a team, and a working knowledge of artificial intelligence and machine learning for image analysis.
- Coursework in computer engineering, computer programming languages, image processing, web development/graphical user interfaces (GUIs) or a related area is desirable.
Eligibility Requirements
