Vie, 03/08/2018 - 11:30
PhD study at the Tasmanian Institute of Agriculture - University of Tasmania (UTAS-TIA) based on Hobart, Tasmania, Australia. The program includes full-funding resources for the high-performance candidate by UTAS-TIA and additional partners. Conduct a PhD program at UTAS-TIA will place you in a unique research environment. We aim to ensure that you not only make an impact on agricultural systems analysis but also develop the skills you need for the career you want at the end of your degree.
The PhD project will provide the development of skills and leadership in the area of bio-economic integrated assessment of irrigated agricultural systems, including the development and application of modelling and mathematical methods for prioritising technology and policy actions in agricultural systems (crops [barley, wheat, potato and pastures] and livestock) at regional scale.
Sustainable land and water management is faced with various challenges at the field, farm and larger regional and market scales. Natural resources are managed at field-scale but policy settings are usually regional or national. Likewise, the scalability of agricultural systems (i.e. methods used to integrate data and models at different scales) is often ignored or only partially represented. This project will investigate how water management impacts crop productivity regionally in Tasmania. We will apply existing model-scaling techniques and assess the drivers of yield variability for diverse Tasmanian agricultural systems. This innovative research will combine strengths in irrigated agriculture at field-scale with multi-scale modelling, multi-model analysis and integrated bio-economic assessments. This project will develop methods which can support improved water risk management and planning with better understanding of the drivers of yield variability and scaling methods.
To be considered as a candidate you will have:
- Undergraduate studies (finished or to finish in no more than 6 months) and research experience in a relevant discipline area, such as agricultural systems, agronomy, environmental sciences, statistics, agricultural economics, geographic information system mapping, mathematical programming with focus on agriculture.
- Knowledge of agricultural systems.
- Demonstrated excellence in research (e.g. posters, papers, fieldwork, etc.).
- Modelling skills (mathematical, biophysical, climate models, etc.).
- Experience writing scientific code in R, Python or equivalent languages, and experience handling large datasets.
- Ability to work effectively and independently as part of a multi-disciplinary and regionally dispersed research team.
If you are interested, please send CV (no more than 2 pages) to email@example.com