As the science of theoretical chemistry has matured, its focus has shifted from analytically solvable problems, such as the atomic structure of hydrogen, to more complex problems for which analytical solutions are difficult or impossible to specify. Important questions about the behavior of condensed phases of matter, the electronic structure of heavy atoms and the _in vivo_ conformation of biological macromolecules fall into this class. The powerful, highly-parallel supercomputers that have evolved from recent advances in computing technology are ideally suited to the mathematical modeling of these complex chemical phenomena. Simulations in which the trajectories of a large number of interacting bodies must be computed simultaneously, such as statistical-mechanical Monte Carlo studies or molecular dynamics simulations, are particularly appropriate for implementation on parallel machines. I plan to devote my graduate and postgraduate work to the theoretical study and computational modeling of these many-body systems.
In preparation for this work, I have developed a strong background in mathematics and computer science in addition to my coursework in chemistry. Given the current demand for increased computing capacity, this background should prove beneficial. For example, while recent advances in computer hardware alone promise potential tenfold increases in speed, truly significant jumps in computing power (speedups of, say, a thousand fold) will require changes in currently available programming environments and the reformulation of popular simulation algorithms. Furthermore, until highly-parallel machines become widely available, even modest increases in capacity will depend in part upon the innovative use of existing hardware through the continued modification of available software and the development of new algorithms. My elective work in computer science and mathematics should prove useful for both the revision of existing programs and the eventual development of new programs and languages specifically designed for the parallel architecture of tomorrow's supercomputers.
After completing my doctoral work, I plan to seek employment as a university professor. I believe the rewards of such a position far outweigh the greater monetary compensation available in industry. For example, academic scientists are generally allowed a greater degree of freedom in their choice of research areas. They also benefit from exposure to co-workers who have a broad range of experiences. Finally, the satisfaction I have derived from my undergraduate tutoring and consulting experience has