Marine Quantitative Ecologist; NOAA NCCOS

Job Title: 
Marine Quantitative Ecologist
Job Location: 
Beaufort, North Carolina
Duration: 
Full-Time
Description: 

Overview

  • NOAA NCCOS seeks highly qualified candidates for a Marine Quantitative Ecologist position on an interdisciplinary research team of contract and federal employees. The integrated research team will support the NOAA National Centers for Coastal Ocean Science (NCCOS) Marine Spatial Ecology Division (http://coastalscience.noaa.gov/), which is a nationally recognized scientific research program that conducts spatial ecological analysis, statistical modeling, ecological forecasting, and predictive mapping to support marine ecosystem management, conservation, and spatial planning. The candidate will be employed via a contract to work at the NOAA National Ocean Service in Beaufort, NC.
  • We seek candidates with demonstrated expertise using scientific analyses of underwater photogrammetry to fit a variety of advanced analytical and statistical models to marine ecological data – including both physical and biological aspects of marine and coastal ecosystems. Experience in marine sciences is strongly preferred, however, candidates with strong backgrounds in remote sensing and spatial/geostatistical environmental modeling will also be considered.  Successful candidates will help conceive and implement solutions to large, complex spatial and spatio-temporal challenges of change detection, including modeling of habitat usage, marine wildlife survey data, and/or physical, oceanographic, and geological aspects of marine habitat. Examples of potential projects include spatial and spatiotemporal modeling of corals, seafloor habitats, estuarine and coastal habitats, and marine ecosystem structure  in a variety of US jurisdictions.

 Core Responsibilities

  • Develop analytical capacity for spatially-explicit analyses of change based on large-area-imagery to address questions of marine management, conservation, and restoration relevance:
    • Design and implement quantitative analyses of large-area-imagery (e.g., Structure-from-Motion) to detect change in indicator metrics of marine benthic species (e.g., occurrence, abundance, size-frequency), marine habitat, and marine ecosystem properties;
    • Develop and implement machine learning algorithms for analyses, including algorithms for model selection, validation, skill assessment, and ground-truthing;
    • Synthesize and interpret outputs and protocols in the context of applied management, conservation, and restoration scenarios problems.
  • Conduct field acquisition of large-area-imagery :
    • Lead or contribute to data collection for underwater imagery based on uncrewed underwater vehicles, uncrewed aerial vehicles, and/or diver-based systems with high resolution image acquisition and other environmental data;
    • Develop and apply statistical and analytical approaches for data integration, including data assimilation and multi-scale approaches for multiple different datastreams;
    • Automate data acquisition, analyses, accuracy assessment, and QA/QC.
  • Contribute to peer-reviewed publications, presentations, and technical memoranda.
  • Provide analytic guidance to team members.
  • Travel to federal and state laboratories, academic institutions, and field missions as part of collaborative research projects (<10% of time).

Qualifications

Required Qualifications:

  • Minimum of Master’s degree or equivalent experience in Ecology, Applied Statistics, Geography, Oceanography, or similar highly quantitative field;
  • High level of expertise executing spatially-explicit photogrammetric analyses of two and three dimensional images
  • High level of expertise executing statistics in R and/or Python (a code sample may be requested to demonstrate proficiency);
  • Demonstrated ability to independently identify, analyze, and solve complex challenges in imagery analyses, working with large data sets and computationally complex tasks;
  • Demonstrated excellence in written and oral scientific communication skills;
  • Demonstrated experience working independently and with a team;
  • Ability to work effectively in a dynamic, fast-paced, team-oriented, multi-project, multi-disciplinary environment;
  • Non-U.S. citizens must possess current documentation authorizing employment in the United States and meet the minimum security requirements for access to federal facilities;
  • A National Agency Check and Inquiries (NACI) background check and fingerprinting will be required.
  • Must be able to pass a drug screen, background check and/or National Agency check. 

Preferred Qualifications:

  • Expert R programmer, with experience in at least one additional relevant language (e.g., Matlab, Python);
  • Ph.D. or additional research experience beyond Master’s;
  • Experience with a range of spatial and statistical photogrammetry analyses techniques including machine learning, geostatistics, and corresponding model selection, skill assessment, and uncertainty characterization;
  • Knowledge of marine science and marine ecosystems;
  • Ecological knowledge of benthic coral reef organisms and species identification;
  • Experience analyzing spatial marine ecological and/or habitat data;
  • Experience with data management and databases, especially for remote sensing and imagery
  • Experience with parallel and high-performance computing in cluster or cloud environments;
  • Record of academic publication;
  • Ability to go to sea aboard a research vessel or other field research
  • Scientific research diving experience (AAUS or equivalent) 

 

CSS is an Equal Opportunity/Affirmative Action Employer who provides equal employment opportunities to all employees and applicants for employment without regards to race, color, religion, sex, gender identity, sexual orientation, pregnancy, national origin, age, disability, veteran status or genetic information. In addition to federal law requirements, CSS complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

 

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