Primary Purpose: The Agronomic Crop Imaging Lab (ACI Lab), University of Saskatchewan invites applications for a three-year postdoctoral fellowship (PDF) under its Research Grant Programs. The selected candidate will contribute to a number of ongoing research projects.

Nature of Work: Combination of desk and fieldwork

Accountabilities: The PDF will play a key role in connecting a dynamic team of soil and crop scientists, GIS specialists, remote sensing experts, and computer programmers. They will be responsible for:

Conducting fieldwork using UAVs (drones) to capture high-resolution imagery and environmental data Processing and analyzing large-scale remote sensing datasets from UAV, satellite, and ground-based sensors Leveraging artificial intelligence, e.g. machine learning, reinforcement learning to develop data-driven, space-time explicit precision agronomic solutions Utilizing high-performance computing (HPC) systems for large-scale geospatial data processing, model training, and validation Designing and managing scalable ETL (Extract, Transform, Load) pipelines to integrate multi-source, multimodal datasets Applying big-data analytic, including spatio-temporal modeling and deep learning techniques Collaborating with an interdisciplinary team of soil scientists, agronomists, and computer scientists Presenting research findings at national and international conferences and contributing to peer-reviewed publications Being part of the new Nutrien Centre for Digital and Sustainable Agriculture

Education: Ph.D. in Plant Science, Environmental Science, Soil Science, Geography, Bioresources, Computer Science, or related discipline

Licenses: A valid class 5 driver’s license is a necessity.

Experience: The candidate should have extensive experience in handling big geospatial datasets, remote sensing, and quantitative research techniques. Strong scientific communication and writing skills are essential. Additionally, the candidate must demonstrate the ability to work independently while collaborating effectively within a team.

Skills: Expertise in varying disciplines, with strong proficiency in programming languages such as R, Python or Javascript is required. Experience in big data analytics and deep learning using time series analysis and spatial interpolation of landscape features in the Canadian Prairie would be considered an asset.

To Apply:
All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority. The University of Saskatchewan is committed to the principles of employment equity. The University encourages applications from qualified Aboriginal people, persons with a disability, racially visible persons, and women.

Please include your curriculum vitae, cover letter, academic transcripts, degree certificate(s), and contact information in your application.