PhD Graduate Research Assistantship in AI-Powered Canning Quality Assessment for Dry Bean Breeding

Department: Plant Agriculture, Ontario Agricultural College (OAC), University of Guelph
In collaboration with: Department of Food Science, University of Guelph
Start Date: Fall 2025
Positions: 1

Key Responsibilities:

• Develop and optimize deep learning algorithms (e.g., convolutional neural networks, recurrent neural networks) to predict canning quality based on seed imaging and sensory rankings.
• Collect and preprocess high-quality datasets, including spectral and regular imaging of dry bean seeds, agronomic data, and lab-based canning quality metrics.
• Collaborate with the Department of Food Science to standardize canning protocols and sensory analysis, including training and coordinating an advisory panel for sensory evaluations.
• Integrate multi-dimensional datasets (agronomic, imaging, lab, sensory) to identify key features influencing canning quality using feature importance methods.
• Assist in field trials, including data collection on disease resistance and agronomic traits, to support the selection of top-performing bean lines.
• Prepare research findings for publication in peer-reviewed journals, present results at national and international conferences (e.g., Bean Improvement Cooperative Meeting), and contribute to knowledge dissemination through workshops and field days.
• Engage with industry partners, growers, and the Ontario Pulse Crop Committee to ensure alignment with registration requirements and market needs.

Master’s Graduate Research Assistantship in Multi-Omics Approaches to Map Seed Coat Color Stability in Dry Beans

Department: Plant Agriculture, Ontario Agricultural College (OAC), University of Guelph
In collaboration with: Department of Biological Sciences, University of Toronto Scarborough
Start Date: Fall 2025
Positions: 2

Key Responsibilities:

• Analyze genome and methylome sequencing data from a diverse panel of cranberry and pinto bean varieties with a broad range of darkening phenotypes.
• Conduct genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS) to identify candidate genes and epigenetic modifications linked to seed coat darkening and stability.
• Utilize hyperspectral reflectance phenotyping to quantify and monitor seed coat color changes over time under controlled experimental conditions.
• Integrate genetic, epigenetic, and phenotypic data using advanced bioinformatics tools to uncover regulatory networks influencing seed coat color.
• Assist in the development, validation, and application of molecular and epigenetic markers for selection of stable, non-darkening bean varieties.
• Contribute to the design, implementation, and analysis of greenhouse and experiments related to seed coat darkening.
• Prepare research findings for publication, present results at scientific conferences, and participate in multidisciplinary team meetings.

Qualifications:

• Bachelor’s degree in Genetics, Molecular Biology, Plant Science, Bioinformatics, Computational Biology, or a closely related field.
• Demonstrated interest or experience in genomics, epigenetics, or plant breeding, with familiarity in genome and/or methylome sequencing preferred.
• Experience with bioinformatics tools and statistical software for the analysis of high-throughput genetic and epigenetic data (e.g., GWAS, EWAS) is an asset.
• Knowledge of or interest in hyperspectral phenotyping and integration of multi-omics datasets.
• Strong analytical and problem-solving skills, with the ability to work independently and collaboratively in an interdisciplinary environment.
• Excellent written and oral communication skills, with a commitment to contributing to scholarly publications and scientific presentations.

Postdoctoral Researcher in Computational Dry Bean Breeding

Department: Plant Agriculture, Ontario Agricultural College (OAC), University of Guelph
Salary: $55,000 - $60,000 CAD per year plus benefits (negotiable)

Responsibilities:

• Analyzing large, complex datasets and developing improved analytical solutions.
• Collaborating with experts in bioinformatics, plant physiology, and breeding.
• Fine-tuning large language models (e.g., GPT, BERT) for data interpretation.
• Conducting indoor/outdoor experiments in phenomics, genomics, and transcriptomics.
• Publishing research papers and presenting at conferences.

Master’s Graduate Research Assistantship in Genomics/Phenomics-Assisted Dry Bean Breeding

Department: Plant Agriculture, Ontario Agricultural College (OAC), University of Guelph
Location: Guelph, Ontario
Start Date: Winter/Spring 2025
Positions: 2

Objectives:

• Investigating the emergence of new anthracnose races or persistence of race 73.
• Developing phenomics and genomics markers for resistance screening.
• Using spectral imaging for rapid, high-throughput screening in early growth stages.
• Enhancing dry bean resilience with molecular markers.