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The Cooperative Institute for Marine and Atmospheric Studies (CIMAS) at the University of Miami, Rosenstiel School of Marine, Atmospheric, and Earth Science invites applications for one Senior Research Associate II (SRA II) position at the NOAA Fisheries Southeast Fisheries Science Center, Advanced Technology Branch located across southeastern US laboratories in Galveston, TX, Pascagoula, MS, Miami, FL, and Beaufort, NC. The Advanced Technology Branch supports the collection and automation of underwater video data processing to support the management of fisheries in the Gulf of America, Atlantic, and Caribbean.

We are searching for a candidate with expertise in the deployment of underwater image systems on fisheries-independent surveys and subsequent development and implementation of artificial intelligence and machine learning analytical pipelines to efficiently process resulting datasets to estimate indices of fish abundance. Duties will include participation in fisheries-independent surveys and leveraging of advanced knowledge of data collection methodologies, fish identification, analytical automation, and data product deliverables to conduct research on artificial intelligence and machine learning techniques to detect, track, and classify fish recorded in underwater video surveys. This position will lead the curation of annotation libraries and oversee model training and evaluation, with particular focus on VIAME software tools and other open source AI/ML methodologies. Development of implementation plans and contributing to presentations, and reports and/or peer-reviewed manuscripts will accompany the progression of research. This position is currently funded for 1 year with possible extension based on funding availability and will be based at a NOAA facility in Galveston, TX, Pascagoula, MS, Miami, FL, or Beaufort, NC. Telework flexibility is available.

Candidates for this position must have: 1) a master’s degree or higher in a field related to biological sciences; 2) at least one year of work-related experience with evidence of participation in fisheries-independent surveys and research focused on the development and implementation of AI/ML methodologies to detect, track, and classify fishes in underwater video data; 3) previous experience working with VIAME software and/or other open source software; 4) ability and desire to work as part of a collaborative team and support a culture of respect, inclusivity, and cooperation; and 5) demonstrated organizational and communication skills.

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