In collaboration with the Department of Fisheries and Oceans Canada, the successful candidate will use a Laser Optical Plankton Counter (LOPC) data stream to identity plankton species in samples from the Great Lakes. A single tow may contain images of 30+ million particles.
The initial focus will be to identify one species of management interest, the invasive spiny water flea, Bythotrephes longimanus. The student will use computationally intensive machine-learning techniques, such as neural networks, in order to classify images. The student will train the algorithm using species from both single and mixed species laboratory populations run through the LOPC, and from lake tow data streams where positive identifications can be made.
The position will start Sept 2018 or Jan 2019. The successful candidate will be funded for 4 years by the Department of Fisheries and Oceans, Canada (www.dfo-mpo.gc.ca) and the University of Waterloo (uwaterloo.ca). Work will occur both at the Center for Inland Waters in Burlington, Ontario and the University of Waterloo, Waterloo, Ontario. A quantitative or computational background will be strongly preferred.
Direct inquiries to Kim Cuddington at the University of Waterloo (kcuddingATuwaterlooDOTca). Applicants must meet the standards for entry into the Biology (uwaterloo.ca/biology/