PhD Top-Up Scholarship in Mine Optimisation and Valuation

A PhD APA Top-Up Scholarship of $7000 p.a. (plus $2000 travel allowance p.a.) is available for 3 years in the area of Mine Optimisation and Valuation. Total value with APA of around $28000 p.a. tax free.

This is a joint UNSW/BHP Billiton endeavour, and represents an excellent opportunity to participate in mathematics research on projects with input from industry. Your PhD work will be motivated by the following two mathematically challenging unsolved problems. Successful applicants should have excellent honours year results and a background in optimisation or operations research. Applications close 31 October, 2005.

The projects involve mathematics in the areas of Operations Research, Optimisation, Integer Programming, Probability/Stochastics, Numerical Analysis, Financial Mathematics, and Mathematical Modelling.

Compression of Optimisation Models: The optimization problems that arise from mining project valuations are huge. Some form of model compression is required if the problem is to become computationally tractable. This compression commonly takes the form of grouping areas of different mineralisation into larger units. The state-of-the-art in grouping technology is at present little better than an educated guess. Poor grouping will lead to poor mining plans that undervalue the mining project. In order to build mine plans of maximum value, efficient optimization model compression methods are required, so that the optimization is tractable, but the model loses a minimum amount of accuracy through this compression. This project will focus on developing structured methods of grouping with good model compression properties.

Uncertainty in Mine Planning: Mine plans are subject to uncertainties on several fronts: the selling price of the commodity, the market volume of the commodity, and the inaccuracy of grade and quality estimates for the minerals underground. Stochastic price and volume models can provide raw data to quantify price and market volume uncertainty. Stochastic grade simulations provide raw data with which to quantify the problem of mineral grade and quality inaccuracy. Mathematical techniques to build optimal mine plans based on stochastic price and grade models are in their infancy. The goal of this project is to develop rigorous optimization and valuation methods that take into account uncertainties in metal price and/or mineral grade. Of particular interest are techniques that build mine plans that can respond rapidly to changing circumstances to maximise the mine's value.



For further details contact:

Dr Gary Froyland, (02) 9385 7050, G.Froyland@unsw.edu.au