Graduate Profile

A Graduate student should be able to:

1. Gain knowledge about the different meanings of the word model; know how to recognize and classify any connotation of this word in the scientific and technological language, as well as have the means to establish analogies of these connotations with others studied, which will allow graduates, in the professional field, to take decisions considering any demand for modeling work.
2. Learn about the various possible types of mathematical and computational models; know the applications of each of them and their relative advantages and limitations; know how to distinguish similarities and differences between these types of models.
3. Know how to choose the mathematical and computational structures relevant to each modeling task and, among these, the most appropriate approach for the objective.
4. Recognize the usual phases of modeling work; learn about the main existing techniques and know-how to choose the most appropriate one for a given situation.
5. Learn how to construct and explore models; master mathematical development techniques, computational implementation techniques, validation techniques, simulation techniques, and model exploration techniques.
6. Know and be used to searching for theoretical and/or practical contributions in scientific publications needed for modeling work.
7. Master how to write articles, as well as scientific communications and technical reports.
8. Develop a solid technical and scientific background that qualifies graduates to carry out scientific and/or technological research in the area of ​​Modeling and Optimization.
9. Develop a solid pedagogical educational background that enables graduates to teach in higher education or post-graduate courses.
10. Develop solid practical training in Modeling and Optimization that enables graduates to practice professionally in the productive and service sectors.
11. Be able to develop computational codes, aiming at process optimization, adapting, reevaluating, and documenting products and productive systems.
12. Be able to plan experiments and process computer simulations.

As it is an area of activity that is intrinsically interdisciplinary, we do not intend to pre-define a rigid profile for the students. However, it is desirable that candidates have general mathematical and computational skills or demonstrate the ability to develop them throughout the course and this is provided by the only two compulsory subjects in the program.

Thus, it is natural to expect that students graduating from Exact Sciences (Mathematics, Computing, Statistics, Physics, and Chemistry) and Engineering (Civil, Production, Electrical, Mechanics, Control and Automation, Mechatronics, Chemistry, Computing) areas will be more prone to apply for the area of concentration, which in no way excludes the possibility of candidates from other areas of knowledge.