Geostatistics uses statistical modelling to assess the uncertainty inherent in natural resource problems. There is always a sparsity of data because of the cost of getting samples. Statistical models have emerged as the preferred method of quantifying the uncertainly in this situation. These models allow mining, petroleum and environmental companies to make better decisions when faced with sparse data. Thus, the intern’s research will develop a methodology to calculate the true distance between samples.
This project involves studying the kinematics of the human body during physical therapies on the arm and shoulder. With guidance and assistance from Glenrose Hospital, the intern will collect a library of typically prescribed motions of the shoulder and arm during physical therapy. He will then develop a mathematical model to represent the kinematics of the arm and shoulder as well as a parameter identification routine to identify the model parameters using simple moves and coordinate measurement techniques.
The intern will collect data on tree mortality in the company's woodlands and develop equations to predict mortality rates from tree growth or forest age and composition. Mortality rates for white spruce have been particularly difficult to obtain due to overall low levels and sporadic occurrence of tree death. This project provides an interesting alternative broad survey approach to mortality compared to the present permanent sample plot (tag and re-measure) program. It will also aid the company with modelling the yield of mixed-wood forests.
Pharmacokinetics, the study of a drug’s course through the body, is an essential quantitative tool used in all stages of drug development and administration. The liver is the primary site of drug metabolism and elimination from the body, but it is difficult to model due to its complex structure. A virtual organ will be developed for the liver using modern mathematical techniques such as fractals in conjunction with flow reservoir modelling software developed by the Computer Modelling Group Inc.
The intern will work on quantifying inherent uncertainties associated with natural attenuation of organic contaminants at upstream oil and gas contaminated sites. Uncertainty and variability in parameters such as hydraulic conductivity, biodegradation rate constant and spatial distribution of the source of contaminants may lead to highly uncertain results to be obtained from routine fate and transport models. Thus, there is a need to quantify these uncertainties and study their impact on the predicted plume size and clean up time.
The internship will concern studying the role and impact of specific proteins (in particular tubulin) in cancer, and the identification of prognostic markers of cancer progression and predictors of cancer response to existing and new compounds (mainly based on microarray data analysis and protein structure prediction).
Microtubules are a key constituent of the cell's structural framework and are responsible for a diverse range of functions within the cell. They are cylindrical polymers, 25 nm in diameter and can grow to be several hundred micrometers in length. Tubulin, the protein which is the main component of microtubules, self-assembles to form the walls of the cylinder in a highly-ordered, helical lattice arrangement. Functionally, microtubules fill a wide variety of roles within the cell. The function often considered most important is the role played in cell division.