Doctor of Philosophy (PhD) in Modeling and Simulation

The Modeling and Simulation PhD is an interdisciplinary degree primarily intended for students with an academic or work background in mathematics, sciences, engineering, or computer science who wish to pursue a career in academia, government, defense, entertainment, technology, service or manufacturing. Simulation is the quintessential utility tool. In one way or another, just about every engineering or scientific field uses simulation as an exploration, modeling, or analysis technique. Simulation is not limited to engineering or science. Simulation is used in training, management, and concept exploration and involves constructing human-centered, equipment-centered, and/or stand-alone computer-based models of existing as well as conceptual systems or processes. The purpose of simulation is to evaluate the behavior of the human, organization, equipment, and/or systems under study through the evaluation of output from the corresponding simulation construct. Because of the scale and complexity of modeling and simulation, practitioners have developed both generalized and specialized skills. Input from industry and government M&S users and developers have been instrumental in identifying the key competencies for M&S professionals and has been critical to the development of this curriculum. The curriculum is designed to provide a broad overall perspective of the developing simulation industry and an awareness of the economic considerations. Upon completion of the program, graduates will have the diverse training necessary to enable them to work in varied capacities in government agencies, or in the defense, service, entertainment, and manufacturing industries. Simulation Modeling and Analysis The Simulation Modeling and Analysis research area attracts those who desire to gain expertise in using simulation as a optimization tool for effective design, planning, analysis, and decision-making. The emphasis of this area is on problem definition, model formulation, design of simulation experiments, and model-based analysis. This area attracts those who seek to develop skills in the application of advanced quantitative methods to modeling and simulation. Building on backgrounds in operations research, mathematics or statistics, they should gain experience in modeling and simulation through the application of optimization, mathematical and statistical theory to build Multidisciplinary simulation models and conducting rigorous simulation experimentation. A graduate will be prepared to work with corporate and government decision-makers as they model and evaluate the impacts of proposed policies and system designs. Typical courses include Engineering Statistics, Statistical Aspects of Digital Simulation, and Mathematical Modeling, Discrete Systems Simulation, Object-Oriented Simulation, Experimental Design, and Quantitative Aspects of Modeling and Simulation.