Scholarship Opportunities
PhD Scholarships
The Soil CRC will be offering over 40 PhD scholarship opportunities.
PhD scholars through the Soil CRC will have opportunities to develop their industry knowledge and relevance, through additional training and networking opportunities associated with the Soil CRC, and will be part of nationwide cohort of Soil CRC postgraduate students. They will have the opportunity to work with researchers, farmers groups and industry from across Australia through the Soil CRC PhD program.
The CRC Program aims to develop and commercialise leading-edge research and produce graduates with hands-on industry experience to help create a highly-skilled workforce.
Our call for PhD Scholarships has closed. Future PhD Scholarships may be funded through Major Investment Rounds as part of projects. Please contact the relevant Program Leader for more information.
PhD Scholarship Opportunities
The following projects have been funded by the Soil CRC are advertising for students.
PhD Topic: Soil Constraint Diagnosis and Modelling
Focus: This PhD Scholarship will contribute to the analysis, modelling and diagnosis of soil constraints across Australian farming systems. The aim of this project will be to develop a soil constraint diagnoses framework that brings together biophysical crop and soil modelling with statistical and artificial intelligence approaches and leverages of public domain and farm level data.
Stipend: AUD $30,000 per annum for a maximum of three years.
University: University of Southern Queensland
Closing date: This scholarship will remain open until the position is filled.
Principal Supervisor: Associate Professor Keith Pembleton (keith.pembleton@usq.edu.au)
EOI Instructions: Before applying for this scholarship, you should first send an email to the Principal Supervisor containing
(1) Your CV, and
(2) an initial research proposal (max. 2 pages) including an identification of the problem, a brief review of relevant literature, and an outline of the proposed research methodology.
PhD Topic: Machine learning, soil hydrology and agriculture
Focus: This research will explore the potential of using data from in situ soil moisture probes to determine hydraulic parameters. The approach will use in situ moisture readings to provide feedback to a soil moisture model being run in parallel, in a technique known as Data Assimilation. This will require application of data cleaning procedures, evaluation and execution of a range of data assimilation procedures including Ensemble Kalman & Particle filter, use of pedotransfer functions, development of field based data training routines, as well as some laboratory analysis of soil properties. In addition to data assimilation, this research will attempt to leverage a range of machine learning and time series analysis techniques to address algorithm limitations when applied to real-world soils.
Stipend: Candidate will be required to obtain a UTAS stipend. Top-up scholarship is available. Operating cost of around $30,000 are available for research.
University: University of Tasmania
Closing date: Mid-December 2020
Principal Supervisor: Dr Marcus Hardie (Marcus.hardie@utas.edu.au)