Start date: September 2020 or negotiable
A fully funded four-year PhD position is available in the ‘Transformative Sensor Technologies and Smart Watersheds for Canadian Water Futures’ project (TTSW) at the University of Waterloo. The position is part of Global Water Futures: Solutions to Water Threats in an Era of Global Change, a large collaborative initiative involving multiple Canadian universities and partner organizations. TTSW aims to develop, test, and employ advanced terrestrial, sub-orbital, and satellite remote sensing tools targeted to support research regarding the emerging spectrum of water related issues throughout cold regions.
More information
The CryoSAR airborne radar system is a new and unique CFI-funded synthetic aperture radar (SAR) system specifically designed to make fully polarimetric and InSAR-capable observations of cold season environments at Ku and L-band frequencies. The successful PhD candidate will explore ways that CryoSAR observations of snow can be used to estimate the distributions of snow water equivalent (SWE) at watershed-scales. To achieve this, the candidate will be expected to develop remote sensing modelling approaches that focus on SWE retrievals from SAR backscatter and InSAR observations. The successful candidate will be encouraged to be an active participant in winter field campaigns in prairie and alpine environments to characterize SWE and snowpack microstructure properties. They will also have access to a dedicated high-performance GPU-based processing system capable of conducting end-to-end SAR processing and SWE retrieval modelling.
The successful candidate will work under the supervision of Dr. Richard Kelly, and will collaborate with researchers at partner organizations involved with the CryoSAR project.
Eligibility
Ideally, you will have a strong background in quantitative remote sensing science, preferably with an understanding of Earth system science processes, especially hydrological science. Ideally, you should hold a degree in geographical science, geophysics, Earth science or engineering. The candidate should have strong analytical capabilities with a high degree of comfort across coding environments such as C, Python, R, IDL, Matlab or other programming languages commonly used in remote sensing. Strong communication skills are essential and the candidate should be able to work both independently and within a group setting both in field environments and in the lab.
Full funding is available for four years, pending satisfactory progress through the PhD program.
Application instructions
Interested applicants should submit a cover letter stating their motivation and experience. In addition, a curriculum vitae, unofficial transcripts, and contact information for three references should be included in a single .pdf file and sent to Dr. Richard Kelly (rejkelly@uwaterloo.ca) with [PhD-TTSW-RichardKelly-2020] in the subject line.
We thank all applicants for their interest. However, only selected candidates will be contacted.