Opportunities

Opportunity: Application of novel airborne Ku and L-band SAR observations for watershed-scale seasonal snow mapping

Start date: 1 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.

Opportunity: Estimation of snow water equivalent from airborne Ku and L-band SAR

Start date: 1 September 2019 or before

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 objective of this PhD project will be to better quantify large-scale distributions of snow water equivalent (SWE) on land across various regions of Canada. In this project, a unique Ku and L-band SAR system called CryoSAR, under procurement through a successful CFI grant, will be deployed in different environments in Canada. The aim of this project is to demonstrate the capabilities of airborne imaging Ku and L-band SAR to create local to regional maps of SWE over several different domain types (tundra, prairie, maritime, alpine, and forested). The remote sensing science will focus on backscatter SAR signatures from these domains and explore InSAR opportunities. The candidate will have access to a unique facility with remote sensing data that are considered highly desirable for novel cold region observation studies.

The successful candidate will work under the supervision of Professor Richard Kelly through his Theoretical and Applied Earth Observation Science Lab, and will collaborate with researchers and private partner organizations for the airborne deployment of CryoSAR during dedicated field campaigns at selected sites from our network of instrumented observatories.

Eligibility

Ideally, the successful candidate will have a strong background in quantitative remote sensing science, preferably with an understanding of Earth system science processes, especially hydrological science. You should hold a degree in geographical science, geophysics, Earth science or engineering will be ideal. 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 expectations. 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 with [PhD-TTSW-RichardKelly] in the subject line.

We thank all applicants for their interest, however, only selected candidates will be contacted.

Applications for a postdoctoral position in the Department of Applied Mathematics at the University of Waterloo are invited. The successful candidate will work on a Global Water Futures funded project on lake ice modelling. Duties will include coupling the Los Alamos sea ice model CICE to the MITgcm and conducting validation studies for Lake Erie.

Eligibility

Candidates should have a background in physical and computational modeling of fluid flows. Strong coding skills and experience with high-performance computing are essential. Experience with couple ice-ocean modelling is desirable. The successful candidate will have the opportunity to work with a multidisciplinary teams involved in other Global Water Futures projects and with government partners. A PhD in applied mathematics, physical oceanography, engineering or a related discipline is required upon appointment. The anticipated start date is January 7, 2019, but is flexible. The salary range for this position is $45,000-$50,000.

Application instructions

Applicants should send a CV and a statement of research experience (one page) to Kevin Lamb at kglamb@uwaterloo.ca, and they should arrange to have two letters of recommendation sent to the same email address. We will review applications as they are received until the position is filled.

The University of Waterloo respects, appreciates and encourages diversity and is committed to accessibility for persons with disabilities. We welcome applications from all qualified individuals including women, members of visible minorities, Aboriginal peoples and persons with disabilities. All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority in the recruitment process.

We appreciate all replies to this advertisement, but only applicants under consideration will be contacted.

Lake Futures seeks  one graduate student (PhD) and one postdoctoral fellow (PDF) interested in research on the causes, impacts and mitigation of water quality issues in the Great Lakes and their watersheds. The successful candidates will work with a multidisciplinary team of researchers at the University of Waterloo, Wilfrid Laurier University, and the University of Windsor as well as with industry, government and community partners. Projects involve a combination of fieldwork, data synthesis and numerical modeling. We are specifically looking for candidates for the following sub-project: 

Project 2: Lake Impacts and Responses (PhD positions)

The overall goal of this project is to advance the predictive understanding and modeling of the biogeochemical responses of large lake systems to changes in nutrient inputs and climate warming at temporal scales ranging from days to decades, with an emphasis on nutrient cycling and the management of algal blooms.

PhD 2.1 will work on nearshore-off shore exchange in Lake Erie, with a focus on modeling the plume from the Grand River, via high-resolution numerical simulations using a three-dimensional numerical model. Applicants are required to have a background in fluid dynamics and computational mathematics. Supervisor: Kevin Lamb

Project 5: Transdisciplinary Integration (PDF position)

The overall goal of this project is to enhance the integration across the WPs of Lake Futures in order to deliver knowledge-based decision support tools and socially acceptable, user-driven solutions.

The primary responsibility of PDF will be to create and apply basin-scale, coupled lake-watershed models to predict nutrient dynamics from headwaters to offshore waters. Specifically, PDF will (a) develop basin scale water quality models for watersheds draining into lakes Erie and Ontario using the HYPE modeling framework, (b) integrate the impacts of watershed and reservoir management on downstream water quality, (c) collaborate with another PDF to integrate the effect of past land use, (d) collaborate with lake modeler Dr. Bocaniov at UW to develop coupled watershed-lake models that can be used to predict the effect of current and future land use and climate on lake water quality.

This position will allow autonomy in aligning the project's broad goals with the interests of the successful applicant. Minimum qualifications are a PhD in hydrology, engineering, earth science, biogeochemistry, agriculture, or geography; and experience with GIS. Preferred qualifications include proficiency in handling large datasets (eg NETCDF files), computer modelling, and biogeochemistry. Initial appointment is for one year; second year is contingent upon funding and performance.

Application Instructions

The applicants should have research experience in the fields corresponding to the particular position to which they are applying, as detailed above. They will work with a cross-university team of researchers and must be effective in a multidisciplinary, team-based environment. Excellent communication and organizational skills are required. To apply to any of the positions listed above, please submit a complete application as a single PDF document to Kirsten Grant (kirsten.grant@uwaterloo.ca), with the subject line: PositionName_your surname.

In your application, please include:

• The position to which you are applying (if you are interested in more than one position, please note that)
• A letter explaining your motivation for applying to the position and how your research interests align with the position(s)
• Curriculum vitae
• Copy of transcript(s)
• Contact information for 3 references

Closing date: Applications will be reviewed as they are received. The positions will remain open until filled.

We thank all applicants for their interest. However, only those individuals selected for an interview will be contacted. 

The University of Waterloo encourages applications from all qualified individuals, members of visible minorities, native peoples, and people with disabilities.