Job Title: Postdoctoral Research Fellow in Agriculture (1)
Location: Saskatoon
Company: Super GeoAI Technology Inc.
Role
We are seeking a Postdoctoral Research Fellow in Agriculture to lead research and development on AI-driven fungicide application strategies in collaboration with university partners and Mitacs. The fellow will focus on building advanced decision-support tools for Fusarium Head Blight (FHB) control and Sclerotinia stem rot management, addressing the critical question of whether, where, and when fungicides should be applied. This role combines applied agricultural science with cutting-edge AI/ML research, bridging academic insight with real-world industry adoption.
Key Responsibilities:
- Lead applied research projects on fungicide application timing and location for disease management in cereal and oilseed crops.
- Design and conduct field experiments in collaboration with universities, research partners, and agricultural organizations.
- Analyze agronomic, environmental, and climate datasets to model disease risk and optimize fungicide recommendations.
- Develop and validate AI-based decision-support tools that determine optimal fungicide strategies.
- Collaborate with AI engineers and data scientists to integrate research outputs into SGA’s commercial platforms.
- Publish research findings in peer-reviewed journals and present at academic and industry conferences.
- Mentor graduate students and research assistants involved in Mitacs-supported projects.
- Engage with industry stakeholders and farmers to validate solutions and ensure practical adoption.
Qualifications:
- Ph.D. in Plant Pathology, Agronomy, Crop Science, or a related field.
- Must have received (or expect to receive) a Ph.D. in Agriculture between October 2020 and April 2026.
- Strong background in plant disease management, particularly Fusarium Head Blight and Sclerotinia stem rot.
- Experience in fungicide efficacy trials, disease modeling, or integrated pest management (IPM).
- Proven ability to design and execute field trials and analyze agronomic datasets.
- Familiarity with statistical analysis and modeling tools (e.g., R, Python, SAS).
- Strong publication record in peer-reviewed journals.
- Excellent collaboration skills, with experience working across academic, research, and industry teams.
- Ability to work independently while driving both research innovation and practical application in agriculture.
This isn’t just academic research—you’ll be leading applied science that defines when, where, and how fungicides are used, directly shaping the future of sustainable crop protection.