{"id":2542,"date":"2026-10-19T20:21:22","date_gmt":"2026-10-19T20:21:22","guid":{"rendered":"https:\/\/www.marine.usf.edu\/tbs\/?page_id=2542"},"modified":"2026-10-19T20:42:47","modified_gmt":"2026-10-19T20:42:47","slug":"spring-2027-undergraduate-research-at-usf-cms","status":"publish","type":"page","link":"https:\/\/www.marine.usf.edu\/tbs\/spring-2027-undergraduate-research-at-usf-cms\/","title":{"rendered":"Spring 2027 Undergraduate Research at USF CMS"},"content":{"rendered":"

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Proposed<\/em> Spring 2027 Internships at the USF College of Marine Science<\/h3><\/div><\/div><\/div>
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Application Development: Vessel Offset Measurement Tool <\/strong>(COMIT)<\/em> \u2013 <\/strong>The resultant product from this internship will be to develop an updated iOS and Android \u2018app\u2019 that calculates a vessel\u2019s offset by measuring the vertical distance between the transducer and the waterline, ensuring the depth sounder readings are true of water depth. Application use will provide more accurate depth measurements during crowdsourced bathymetry collection and improved confidence in navigation and survey data.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

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Fish Diet and Contaminant Analysis<\/strong> (TBS)<\/em> \u2013 <\/strong>Lab-based analysis of red drum and sea trout stomach contents to identify and document prey items as part of an ongoing fish diet and contaminant study. Intern will learn dissection, species and organism identification, specimen photography, and accurate recordkeeping under staff and graduate student mentorship. The project builds hands-on laboratory skills while emphasizing careful sample handling and prevention of cross-contamination.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

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Tampa Bay Observing Network (TBON) Water Quality Monitoring <\/strong>(OCL)<\/em> \u2013 <\/strong>Assist with small-boat fieldwork to deploy and service water-quality sondes, collect water samples, and support laboratory chlorophyll-a analysis. Intern will gain hands-on experience with environmental monitoring equipment, sensor maintenance and calibration, and applied water-quality data collection. The project provides field and laboratory experience in coastal monitoring while working alongside technicians and students, including a former Corridor intern.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

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Machine Learning and AMOC Reconstruction <\/strong>(OCLIM) \u2013<\/em> The Atlantic Meridional Overturning Circulation (AMOC) is an important component of the global climate system. The student will leverage existing ocean observations, high-resolution ocean model data, and advanced machine-learning algorithms to reconstruct the AMOC in the subpolar North Atlantic, a critical region for understanding AMOC variability. The project provides interdisciplinary training at the intersection of artificial intelligence and physical oceanography.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

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Stay tuned for official announcements!<\/strong><\/p>\n<\/div>

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