About the Project

James Cook University, in collaboration with the ARC Training Centre in Plant Biosecurity, invites applications for a fully funded PhD position to revolutionize weed management in sugarcane farming using cutting-edge technologies in remote sensing, drone imagery, and artificial intelligence (AI).

Key Objectives:

• Improve Weed Management: Develop an automated platform to map weed distribution using drone imagery and generate precise spray maps.
• Enable Proactive Strategies: Use satellite and drone technologies to track the spread of weeds at paddock, farm, and district levels, facilitating proactive and efficient management approaches.
• Technology Integration: Create AI models for weed detection, integrating these into InFarm’s processing pipelines for commercial-ready solutions in the sugarcane industry.

This interdisciplinary project combines agricultural technology, AI, computer vision, and remote sensing to address critical challenges in weed detection and management. It also offers an exciting opportunity to work at the forefront of sustainable agricultural practices in tropical North Queensland.

Research Approach and Responsibilities

The selected candidate will:

• Develop and train AI detection models, such as object detection and instance segmentation, using state-of-the-art techniques like Convolutional Neural Networks and vision-language models.
• Analyze satellite and drone imagery to detect and map six target weed species in sugarcane paddocks across North Queensland.
• Create and implement algorithms for generating weed maps and spray maps for targeted spot-spraying solutions.
• Collaborate with InFarm for drone image data capture and integration of AI models into their processing pipeline.
• Conduct fieldwork at SRA Meringa Research Station in Gordonvale, QLD, and process pre-trial imagery using small drones to optimize project outcomes.

Eligibility Requirements

We are hiring a highly motivated candidates with:

• A background in one or more of the following areas:
  • Deep learning
  • Computer vision
  • Remote sensing
  • Drone imagery analysis and drone piloting skills
• Proficiency in programming for AI applications (e.g., Python, TensorFlow, PyTorch).
• A strong interest in applying technology to solve real-world agricultural challenges.
• Excellent problem-solving and analytical skills.
• Effective communication and teamwork abilities.

What We Offer

• Fully Funded Opportunity:
  • Stipend: AUD $40,000 tax-free per year for 3.5 years.
  • Additional operating and travel budgets.
• Work Environment:
  • Collaboration with leading experts in plant biosecurity, AI, and remote sensing.
  • Fieldwork at the SRA Meringa Research Station and access to state-of-the-art drone and imaging technologies.
• Professional Development:
  • Attend Centre Forums, Training Retreats, and conferences across Australia.
  • Network with peers and professionals in the scenic and tropical settings of North Queensland.
• Career Opportunities:
  • Develop expertise in AI-driven solutions for agriculture with a clear pathway for commercialization.

Application Process

Interested candidates should submit an expression of interest form on the Plant Biosecurity Training Centre website by January 22, 2025.

Required Documents:

• CV highlighting relevant experience.
• Academic transcripts.
• Statement of purpose detailing your interest and qualifications for the project.