Postdoctoral Researcher to study structure and function of trees using drone-based remote sensing
We are hiring a Postdoctoral Researcher to study structure and function of trees using drone-based remote sensing in the Genome Canada funded FastPheno project
In the FastPheno project we combine high-throughput drone-based phenotyping platforms, plant ecophysiological and genomics approaches to understand forest dynamics and tree resilience to climate change impacts.
The Postdoctoral Researcher will work closely with researchers from the University of Toronto, Université Laval, Natural Resources Canada, and the Ministry of Forests, Fauna and Parcs of Quebec.
The postdoctoral fellows will take leads in the FastPheno project activities on drone- based collection and processing of hyperspectral and LiDAR data from multiple experimental field sites and forest stands located in Quebec and Southern Ontario.
Candidates must hold a PhD in remote sensing, plant biology, forestry, or a related field. Strong background in photosynthesis, ecophysiology, leaf traits, remote sensing and big data analysis and experience with machine learning algorithms is required.
Experience with retrieval of plant physiological and structural information using hyperspectral or LiDAR information is an advantage.
Postdoctoral candidates must have received their PhD after January 2018. Candidates must have strong verbal and written communication skills, willingness to work independently and in a collaborative team environment, and proven capability to publish in peer-review journals
Applicants should send their CV, a list with the names and contact information of 2-3 references and a max. one1 page motivation letter in a single PDF file to email@example.com. Use the words "FastPheno Postdoc Application" in the subject line of your email. The Deadline for submitting your application is September 16th, 2022, however, applications will be accepted until the positions are filled.