Postdoctoral Research Associate In Agricultural Robotics
Vor 2 Tagen
Postdoctoral Research Associate in Agricultural Robotics for Vegetable Breeding: Digital Phenotyping and Digital Twin Leads Locations: Chippendale Time Type: Full time Posted on: Posted 30+ Days Ago Job Requisition ID: 0127605 Located on the Camperdown campus with trips to Victoria for field trials and The Netherlands for additional testing phases.
Collaborate with global leaders in vegetable breeding.
Full time, fixed term for 3 years.
Offering a base salary of $109K - $145K + 17% superannuation.
About the Opportunity ARIAM Research Hub at the University of Sydney, in collaboration with Rijk Zwaan, seeks to transform breeding operations through the integration of advanced robotics and digital twin technologies.
We invite applications for two Postdoctoral Research Associate positions to lead innovative research in robotics, advanced sensing, and optimisation, focusing on AI-driven phenotyping and digital twin modelling to enhance crop traits and breeding efficiency.
You will integrate sensing, sampling, and optimisation technologies into a cohesive system, engaging directly with Rijk Zwaan farm managers and breeders to address practical challenges, such as robot adaptation to specific site conditions and targeting key phenotypic traits.
This collaborative framework ensures that the research is both technically rigorous and practically transformative, bridging the gap between academia and industry to deliver impactful agricultural robotic solutions.
Digital Phenotyping Lead Deploy and integrate RGB, multispectral, and MWIR sensors on autonomous ground robots for real-time phenotyping.
Incorporate a smart soil-sampling module on the ground robot for real-time soil property assessment.
Develop machine learning algorithms for real-time analysis of plant, soil, and environmental data.
Integrate multi-modal data for a holistic assessment of crop health and performance.
Collaborate closely with Rijk Zwaan breeders to align sensing technologies with key phenotypic traits.
Digital Twin Lead Develop predictive algorithms to identify optimal robotic sampling points.
Design and implement digital twin models that integrate soil, crop, and environmental data.
Refine robotic sampling strategies to improve precision and efficiency.
Adapt digital twin models and robotic sampling protocols to various operational environments.
Validate and iteratively refine digital twin models using field data.
Core Challenges Translating complex research objectives into reliable, deployable systems.
Coordinating multidisciplinary teams across multiple geographic locations.
Collaborating with industry stakeholders to align research outcomes with operational goals.
Balancing the pursuit of innovation with the need for scalability and commercial viability.
About You We are seeking candidates with a strong technical background and a passion for impactful research and innovation.
Key qualifications include: PhD in robotics, computer science, computer vision, or advanced remote sensing.
Expertise in autonomous systems, sensing technologies, or digital twin frameworks.
Strong leadership and project management abilities.
Experience working with industry partners and international collaborators.
Specific Expertise: Digital Phenotyping Lead: Expertise in sensing technologies, computer vision, machine learning, and robotics within a real-time field context.
Digital Twin Lead: Expertise in complex systems modelling for digital implementation and optimisation algorithms.
How to Apply Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page.
For a confidential discussion about the role, please contact Rebecca Astar or Cherie Goodwin, Recruitment Operations by email to ******.
Applications Close: Saturday 01 February 2025 11:59 PM EEO Statement: At the University of Sydney, we strive to create a diverse and inclusive community.
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