Soil moisture and plant available soil water (PAW) is a foundational data to predict crop production and inform tactical and strategic decisions on farm management and system design. There are several methods to monitor or estimate soil water and PAW e.g. sensors, proximal sensing, remote sensing, modelling (process based & artificial intelligent) across filed and soil profile, each with their particular limitations and uncertainties. This PhD research will explore issues for uncertainty analysis of soil moisture and PAW at sub-paddock scale and implications of uncertainty from different observations and modelling approach. How high spatial variabilities will constraint model calibration and accurate estimations.
- Stipend (living allowance), valued at AUD $30,000 per annum, tax free.
- Full tuition fees for a period of 6 semesters (full-time equivalent). Domestic students will be allocated a Research Training Program (RTP) Fees Offset Place, whereas international students will be offered an International Fees Research Scholarship.
- The maximum period of the award is three years.
- Working in a research project gaining practical and industrial experience.
To be eligible applicants must:
- be either an Australian citizen, permanent resident or international student;
- not hold a qualification regarded by the USQ to be equivalent to a PhD;
- have a qualification regarded by USQ to be equivalent, or at higher level to a Bachelor Degree with First Class Honours;
- be eligible to be enrolled, full-time on-campus (Toowoomba) in a PhD;
- not be in receipt of similar funding from the Australian Government;
- be native English speakers and/or meet USQ’s English Language Requirements.
- Background in soil physics, hydrology, engineering or natural science with a strong background in statistical analysis
- Experience with modelling (including model calibration and uncertainty analysis) and machine learning is highly preferred
- Familiar with at least one programing/scripting code e.g. R, python, C#
- Excellent communication skills and ability to work in a team
Applicants will be required to send a cover letter and a targeted CV to Dr Afshin Ghahramani
by email. Relevant qualifications, skills and areas of expertise will be provided in the targeted CV.
Applications close 31 March 2021.