• Advanced methods of data analysis;
• Computational statistical methods;
• Modeling the behavior of software systems;
• Discrete event simulation;
• Visualization and validation in simulation;
• Parallel and concurrent calculus;
• Formal methods in programming languages;
• Simulation methods;
• Cooperative intelligent agents;
• Mathematical modeling;
• Modeling of economical processes;
• Simulation languages.

• Training in the modeling and simulation of various types of problems;
• Acquisition of the mathematical knowledge necessary in order to tackle complex problems;
• The acquisition of in-depth knowledge in the modeling / design / implementation of complex applications aimed at simulating various aspects and solving problems specific to natural sciences or economics;
• The acquisition of specialized knowledge in the analysis and improvement of software processes;
• Professional modeling for team work as well as interdisciplinary approaches to research and development.

• Advanced knowledge of theoretical, methodological, and practical developments in computer science;
• Systematic use of computer science knowledge to model and interpret new situations, within application contexts larger than the known ones;
• Detailed knowledge and integrated use of conceptual and methodological apparatus pertaining to informatics to provide solutions for incompletely defined situations, to solve new theoretical and practical problems;
• Proficient use of verification, validation, and evaluation criteria and methods to his/her own software solutions, ability to formulate value judgments and to justify/explain constructive decisions;
• Use advanced skills to develop and conduct complex software projects, of practical and/or research nature, using a wide range of quantitative and qualitative methods;
• Advanced communication skills within different professional environments, appropriate use of computer science vocabulary, good English knowledge;
• Team work abilities, assuming different execution and leading roles, performing professional tasks with considerable amounts of autonomy and responsibility.

Specialty competences:

• Demonstrate advanced modeling skills for economic, industrial, scientific phenomena and processes, by using fundamental mathematical, statistical, and computer science knowledge;
• Demonstrate advanced skills to analysis, design, and construction of software systems, using a wide range of hardware / software platforms, programming languages and environments, and modeling, verification and validation tools;
• Demonstrate advanced skills to apply simulation for solving real phenomena and to develop and build procedures for efficient use of statistical methods;
• Demonstrate advanced skills to apply methods for data analysis and processing, data mining, pattern recognition;
• Ability to teach students in high schools computer science concepts and theories, provided that the holder of the dissertation diploma owns a graduation certificate of the pedagogical education module.