Center for Computational Toxicology and Exposure, Great Lakes Toxicology & Ecology Division
Variability of physical and biogeochemical properties in large lakes takes on a wide range of both temporal and spatial scales, and most classical sampling techniques (e.g., shipboard CTD, moored equipment) are incapable of resolving much of the interesting dynamics expressed in a variety of fields. Processes and features best resolved at high spatial and temporal scales include time-dependent sediment resuspension, the structure of the deep chlorophyll maximum, upwelling events, and other coastal-offshore linkages. New platforms such as autonomous underwater gliders can start to fill this gap. However, while glider technology becomes increasingly commonplace in the world oceans, there are still only a few being used for large lake research. The successful candidate will be responsible for designing and implementing a glider-based observational program to be conducted in conjunction with other CSMI (Coordinated Science and Monitoring Initiative) investigators during the Lake Superior 2016 CSMI. They will also have access to several years of archived glider data (available in the sponsoring PI’s lab) for broader analysis of the processes and structures discussed above. The successful candidate is expected to work closely with academic collaborators (Jay Austin, University of Minnesota Duluth), present results at national and international conferences, and publish research findings.
Autonomous underwater vehicle; Physical limnology; Oceanography; Biogeochemistry;
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