The School of Climate Change and Adaptation & the the Canadian Centre for Climate Change and Adaptation at the University of Prince Edward Island (UPEI) is seeking highly qualified applicants for two post-doctoral fellow research associate positions in climate smart agriculture technologies, hydrology, machine learning, deep learning, integration of models and water management. The UPEI\' School of Climate Change and Adaptation is a new 45,000 square-foot research facility being built in the community of St. Peter\'s Bay, Prince Edward Island. The facility and the lands surrounding it will serve as a living laboratory that allows for unlimited access to nearby wetlands, forests, and coastal habitats. The Centre will be a world leader in understanding and adapting to climate change impacts in relation to food security and sustainability. These appointments are subject to final budgetary approval.
The focus of this Post-Doctoral Fellow Research Associate appointment will be on developing climate smart agriculture practices to measure and map soil properties and plant characteristics in real time for agricultural systems. In particular, the potential candidate will support the research toward the development of smart technologies to ensure food security and sustainability. The incumbents will perform tests using a variety of field and laboratory equipment; hydrological modelling, water balance, soil health, mitigation strategies for climate change, computational and GIS analysis, calibrating and maintaining instrumentation; remote sensing, preparing, and processing field samples for analysis; participating in the collection of field samples throughout eastern Canada, assisting in data analysis, manuscript writing, and preparing scientific technical reports. The successful candidates will interact with researchers and stakeholders with respect to the related research projects.
Qualifications:
The candidates for this post-doctoral fellow research associate must have a PhD in agricultural engineering/water resource management or related disciplines by the start of the fellowship. The potential candidates should have a demonstrated record of scholarship and an excellent track record in research publications. The candidate should have solid background in computer programming, hydrological modeling, software skills, electronics and instrumentation, and agricultural machinery/systems development. Outstanding hands-on skills, strong computational and problem-solving skills, and high level of analytical ability are expected. The candidate should have experience with the operation of laboratory and field equipment, as well as a willingness and ability to work in the field.
The selected applicant must have:
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