Student Profile


The Master of Science in Systems Engineering program is designed to offer professionals of different fields of engineering (industrial, systems, mechanical, electrical, civil, chemical, etc.) and science (mathematics, statistics, economics, computer science, etc. ), a general methodology for scientific supporting to decision-making systems in complex interdisciplinary environments. The student entering this program is required to have a solid foundation in mathematics and computing. It is desirable that the candidate is familiar with a high-level programming language and able to read and understand technical material written in English.  For the doctoral level, in addition to the above, the applicant must possess skills and spirit to conduct original high-level research.

Graduate Professional

The graduate of the masters program is able to solve decision-making problems in which it is necessary to have a more effective allocation of resources. Such problems arise in academia, government, and industry, in settings where the decision variables are restricted in complex ways. The graduate is able to model, describe, analyze, design, manage, and develop solution techniques to such problems. He/she learns quantitative techniques that emphasize problem formulation in a dynamic and uncertain operating environment, and apply them to successfully address and find the best decision making course of action for the achievement of the objectives or goals set, while maintaining the system in an acceptable level of reliability and quality. The graduate professional is trained to identify and define the problem, to use and/or develop quantitative techniques and to discuss solutions derived from these techniques in order to achieve its implementation in practice.

For the doctoral level, in addition to the above, the graduate is able to perform original high-quality research, extending the state of the art knowledge in an area or sub-field of systems engineering. The graduate is able to propose and develop analytical techniques based on an effective exploitation of the problem/system mathematical structure.

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