University of Melbourne and Agriculture Victoria Research

Three PhD research fellowships

The successful candidates will receive:

  • A $33,000 p.a. (tax-free) scholarship for up to three and a half years
  • Professional development programs
  • Access to state-of-the-art technologies

The PhD fellowships will be based at the Australia’s Grains Innovation Park, Horsham, Victoria

Digital imaging techniques for root architecture phenotyping
The PhD candidate will test and develop innovative high-throughput systems for root phenotyping in wheat. Digital imaging techniques are being developed in our lab with the aim towards using spectral signatures to provide valuable information on the physio-chemical properties of roots. The candidate will optimise plant growth media for wheat root phenotyping, evaluate proposed digital phenotyping tools on wheat roots, develop analytical workflows for root architecture modelling, and determine the correlation between desirable root characteristics and above-ground traits. The candidate will also investigate the potential of root phenotyping for nitrogen and water use efficiency estimation in wheat breeding research.

Optimise UAV-hyperspectral system for high-throughput crop phenotyping
The PhD candidate will optimise a hyperspectral sensor system integrated on UAV platforms for high-throughput field phenotyping in grain crops. The candidate will evaluate the performance of the hyperspectral sensor system, considering factors such as data sampling rate, field-of-view, sensitivity and modalities required for sensor operation. This will be followed by validation of the hyperspectral system using in-field ground truth measurements and optimisation of processing workflows for feature selection, image fusion and image classification, as well as calibrating sensor outputs to generate target phenotypic traits. The candidate will identify suitable work packages in MATLAB, Python or R environments and use them to develop data processing and analytical algorithms tailored to generate traits of interest. The optimised hyperspectral system and analytical workflows will be deployed in grain crop breeding and research.

Optimise UAV-LiDAR system for high-throughput crop phenotyping
The PhD candidate will optimise a LiDAR sensor system integrated on UAV platforms for highthroughput field phenotyping in grain crops. The candidate will evaluate the performance of LiDAR sensor system, considering factors such as data sampling rate, field-of-view, sensitivity and modalities required for sensor operation. This research will identify best practises in data processing and analysis for plant phenotyping, including generation of point cloud metrices, morphological indices, segmentation, voxelization, classification, and 3D reconstruction. The candidate will develop analytical workflows to extract traits of interest for grain crops. The LiDAR system will be validated using in-field ground truth measurements and calibrate sensor outputs to generate crop specific phenotypic traits. It is expected that the optimised LiDAR system will be deployed across breeding research for different grain crops.

For questions on research projects please contact:

Dr Surya Kant | Senior Research Scientist, Agriculture Victoria | Principal Fellow,
The University of Melbourne
T: +61 03 4344 3179 | M: +61 0409 577 857 | E: surya.kant@agriculture.vic.gov.au

For enquiries and to apply, please forward a covering letter, your curriculum vitae (please include evidence of research writing such as publication details) and academic transcripts to: Kendra Whiteman Visitor and Student Coordinator, Agriculture Victoria Research Kendra.whiteman@agriculture.vic.gov.au, +61 03 9032 7065

posted: 11 October 2019     Please mention EARTHWORKS when responding to this advertisement.