Mathematical modelling in mining industry
School of Mathematical Sciences and CSIRO Computational InformaticsPosted on: Sun Dec 22 2013
The UTS School of Mathematical Sciences and CSIRO Computational Informatics are seeking a PhD student to undertake research on optimisation in planning and management of minerals extraction and processing under uncertainty. The successful applicant will be awarded a highly competitive $30,000 per annum scholarship plus access to the unique doctoral training program under the auspices of the Industry Doctoral Training Centre in Mathematics and Statistics (visit http://www.gradschool.uts.edu.au/atn/ for more information).
Australia has the world's largest reserves of mineral sands, brown coal, nickel, lead, silver, uranium, iron ore, zinc and other minerals. Australia is ideally positioned within Asia-Pacific, the fastest growing region in the world. Unprecedented demand for commodities from the region has driven high levels of investment in minerals exploration and project developments. Australia's abundant mineral resources, advanced mining equipment, technology and services industry, and proximity to the rapidly growing markets, have made it a world leading mining nation.
The challenges of modern mining industry include a need for sophisticated technologies to extract minerals from low-grade ores, managing labour cost and increasingly focus on environmental sustainability. The costs associated with processing technologies must account for high level of uncertainty resulting from market conditions and ore quality. These risk factors have a significant impact on the profitability of mining projects, whose optimization focuses on correct choice of both, the operating policy and long-term strategic decisions. In this framework, optimising investments and decision-making are challenging and interesting stochastic control problems.
This project focuses on mathematical models and efficient methods for numerical treatment of control problems arising in the decision-making process in the minerals industry. On practical side, these models and methods are of crucial importance for individual policy optimization. On the theoretical side, this research offers a unique opportunity to break in into a highly interesting, versatile and active area of modern mathematics, where practical questions challenge cutting-edge theoretical approaches. Being placed between real option theory, quantitative risk management, and Markov decision theory, the potential impact of this work is substantial and can position the student extremely well, beyond the award of a PhD degree. The quantitative known-how in these field provides an ideal starting point for both a future work in the financial industry, consultancies, minerals business and/or a career in academia.
This PhD research project is a collaborative arrangement between UTS and CSIRO and will be supervised by A/Professor Juri Hinz (UTS) and Dr Tanya Tarnopolskaya (CSIRO).
- First class honours or equivalent in mathematics or other relevant discipline.
- Demonstrated academic ability in statistics, stochastic processes and model implementation.
- Sound knowledge of computer languages, at least one from C++, R, Mat lab, Python, Java
How to apply
Please send an email to both supervisors:
**Mention you saw it on the AustMS website**