Current Opportunities
Summer 2026 Research Positions (2) – AI and Scientific Computing (USask Students Only)
The Razavi EnviroFutures Lab at the University of Saskatchewan conducts research on advanced computational approaches to water systems modelling. The successful candidates will work with Dr. Saman Razavi in collaboration with researchers from the Global Institute for Water Security (GIWS), the School of Environment and Sustainability (SENS), and the Department of Computer Science at the University of Saskatchewan.
We are seeking two highly motivated senior undergraduate or graduate students in Computer Science, Software Engineering, or a related field to join our research team for Summer 2026. The positions will contribute to cutting-edge research on AI-enabled flood modelling and high-performance hydrodynamic simulation.
Students will work on advanced computational tools for flood modelling and prediction, combining deep learning, high-performance computing, and hydrodynamic simulation.
Position 1 – Deep Learning for Flood Inundation Prediction
This project focuses on developing deep learning models (CNN / ConvLSTM) for rapid flood inundation mapping and prediction. The student will work with large spatial datasets generated from hydrodynamic models and remote sensing and develop machine learning models that emulate complex flood simulations.
Responsibilities
- Develop and train CNN and ConvLSTM models
- Implement training pipelines using PyTorch
- Work with large geospatial raster datasets
- Run large-scale training experiments on GPUs and HPC systems
- Evaluate prediction accuracy and model performance
Required Skills
- Strong programming in Python
- Experience with deep learning frameworks (PyTorch or TensorFlow)
- Familiarity with machine learning and neural networks
- Experience with GPU computing
Preferred Skills
- Experience with spatiotemporal modelling
- Experience with geospatial data
- Experience running jobs on supercomputing / HPC environments
Position 2 – Scientific Computing and Hydrodynamic Model Automation
This project focuses on improving the efficiency and workflow of hydrodynamic modelling systems. The student will work on optimizing modelling codes written in C++ and Python, automating modelling pipelines, and developing tools (including graphical user interfaces) that facilitate running large modelling experiments.
Responsibilities
- Improve efficiency of C++ and Python modelling codes
- Develop automated pipelines for hydrodynamic simulations
- Implement tools for ensemble and batch model runs
- Develop graphical user interfaces for modelling workflows
- Improve reproducibility and structure of research software
Required Skills
- Strong programming in C++ and Python
- Familiarity with Linux environments and scripting
- Experience with software engineering and code organization
Preferred Skills
- Experience with scientific computing
- Experience with parallel computing or HPC
- Experience with GUI development (Qt, PyQt, etc.)
Position Details
- Duration: Approximately 4 months (Summer 2026) with the possibility of extension
- Location: Razavi EnviroFutures Lab, University of Saskatchewan
- Eligibility: Senior undergraduate or graduate USask students in Computer Science, Software Engineering, or related fields
How to Apply
Please email your application to: Saman Razavi (saman.razavi@usask.ca) and Andrea Knibbs (andrea.knibbs@usask.ca). Your email subject line must include the phrase: RAZAVI-LAB-SUMMER-2026.
Please include:
- CV
- Unofficial transcript
- Short statement of interest (1–2 paragraphs)
- GitHub or coding portfolio (if available)
Applications will be reviewed as they come in until the positions are filled.
Only shortlisted candidates will be contacted for further steps in the recruitment process.
The Razavi Lab is committed to the principles of equity, diversity, and inclusion, and fosters a welcoming community for all.