About program

The Pos-Graduate Program in Computational Modeling (PPGMC) is a stricto sensu pos-graduation program dedicated to advanced training and interdisciplinary research in computational modeling, applied mathematics, and related scientific domains. Since its inception, the program has been recognized for its commitment to academic rigor, innovation, and the integration of cutting-edge research with the needs of both the Brazilian Northeast and the broader international scientific community.

Established in 2012, the PPGMC received initial accreditation from the Coordination for the Improvement of Higher Education Personnel (CAPES)—the Brazilian federal agency responsible for quality assurance in pos-graduate education—with a rating of 3 on a national scale of 3 to 7. This accreditation authorized the launch of the master’s program. Through steady growth in research output, faculty qualifications, and collaborative networks, the program achieved a rating of 4 in the 2020 CAPES evaluation. This result, indicative of consolidated academic quality, led to the authorization of its doctoral program in 2024.

In Brazil, CAPES evaluates all pos-graduate programs every four years, using a rigorous assessment process informed by Area Documents prepared by specialized academic committees (e.g., the Interdisciplinary Committee). These documents define the key performance indicators and benchmarks for each academic field. A rating of 3 reflects satisfactory performance, typically authorizing only a master’s degree; ratings of 6 or 7 denote programs comparable to the highest-ranked graduate programs worldwide.

The PPGMC’s evolution—from its initial accreditation to the establishment of both master’s and doctoral offerings—demonstrates its sustained dedication to excellence, international relevance, and the formation of highly qualified professionals capable of contributing to scientific and technological advancement. The program evolved and reached a score of 4 in the 2020 evaluation, which allowed the opening of the doctoral program in 2024.

Mission

The mission of the Pos-Graduate Program in Computational Modeling (PPGMC) is to educate and prepare highly qualified professionals at the master’s and doctoral level to contribute to higher education teaching, scientific research, and the advancement of technological development. This mission is pursued through the application of computational models and scientific simulation to address complex problems in the sciences and engineering.

The program emphasizes the conception and development of mathematical and computational models, the formulation and implementation of numerical methods, the use of advanced computational techniques and tools, and the rigorous validation of both numerical and experimental solutions.

This overarching mission is further articulated through a set of specific objectives designed to integrate theoretical knowledge, methodological innovation, and practical application in diverse interdisciplinary contexts:

• check Provide a solid foundation in the mathematical and computational principles of modeling, with applications to problems in the sciences and engineering;
• check Enable the training and professional development of researchers in interdisciplinary fields, with an emphasis on scientific computing applied to problems in the sciences, engineering, and their interfaces;
• checkPromote the development of skills and competencies for the practice of higher education teaching;
• check Foster initiative, entrepreneurship, and the ability to work in multidisciplinary and collaborative teams among graduates of the program;
• check Equip graduates with the capacity to design, develop, and implement models and systems of high scientific and technological complexity;
• checkContribute to strengthening the State University of Santa Cruz (UESC) and consolidating its role as a regional leader in computational modeling and high-performance computing.

Research Areas

The Pos-graduation Program in Computational Modeling (PPGMC) encompasses three research lines within a single area of concentration: Computational Modeling. These lines reflect the expertise of the program’s permanent faculty members and are strategically aligned with the objectives of the Institutional Development Plan, with a strong emphasis on contributing to regional development while maintaining national and international relevance.

Computational Intelligence and Applications

This research line focuses on developing techniques and systems capable of simulating or exhibiting intelligent behavior. It encompasses diverse areas of investigation, such as machine learning, pattern recognition, artificial intelligence, robotics, and cognitive computing. Computational intelligence can be applied across a wide range of domains, including healthcare, finance, transportation, and cybersecurity.

One of its primary areas of application is machine learning, which enables systems to learn from data and improve their performance without explicit programming. Research in this line also supports the development of advanced systems using technologies such as computer vision, speech recognition, natural language processing, and robotics. The overarching goal is to create systems capable of interacting with and assisting humans in a more efficient and natural manner. Applied computational intelligence can enhance efficiency, automate processes, and support informed decision-making, as well as contribute to solutions for social and environmental challenges. This is an inherently interdisciplinary field, requiring expertise in mathematics, statistics, computer science, and the specific knowledge of the application domain.

Mathematical and Computational Modeling

This line of research is dedicated to the design and application of mathematical models, algorithms, computational codes, and scientific computing techniques through an interdisciplinary approach that integrates mathematical and computational concepts to model and simulate real-world and conceptual problems. Such models draw on concepts from physics, chemistry, biology, engineering, economics, and finance.

Mathematical and computational modeling enables researchers to better understand the underlying phenomena of systems and predict their behavior. It is also employed to optimize processes and support decision-making, making use of advanced optimization and simulation algorithms. Applications include, but are not limited to, complex problem analysis, nuclear engineering (fission and fusion), medical physics and numerical dosimetry, nuclear waste treatment, knowledge diffusion and transfer, petroleum engineering, oceanic and atmospheric circulation, pollutant and contaminant dispersion, and the dynamics of biological systems. As a powerful research and development tool, mathematical and computational modeling supports decision-making and performance enhancement across a variety of systems.

Computational Techniques and Simulation

This research line addresses the development and application of scientific computing techniques, high-performance computing (HPC), signal processing, and computational fluid dynamics to design and implement models, algorithms, and computational codes for deterministic and probabilistic modeling of phenomena relevant to science and engineering applications.

The resulting models and tools aim to deliver stable and accurate numerical solutions for problems such as particle transport, radiative transfer, plasma dynamics, diffusive-convective-reactive processes, heat and mass transfer, fluid flow, complex systems analysis, multiscale phenomena, and complex biological systems.

A Brief History

The State University of Santa Cruz (UESC) is an autonomous institution of the Government of the State of Bahia and the only fully established public institution for research, higher education, and extension activities located entirely within the Southern Coastal Mesoregion of Bahia, a region with a population of approximately 2 million inhabitants. The university campus is situated between the two main urban centers of Southern Bahia, at kilometer 16 of the Jorge Amado Highway (BR-415), in the municipality of Ilhéus.

Its geo-educational area covers a vast territory, encompassing the subregions known as the Lower South (11 municipalities), the South (42 municipalities), and the Extreme South (21 municipalities) of Bahia. Altogether, this comprises 74 municipalities, an area of 55,838 km²—representing 9% of the State’s territory and approximately 16% of its population. In just over 20 years as a university, UESC has significantly expanded its research and teaching capacity, with a substantial increase in faculty researchers dedicated to solving complex problems. This has resulted in the establishment of 33 stricto sensu graduate courses, organized into 26 pos-graduation programs covering all CAPES knowledge areas. Among these are 8 doctoral programs, 18 academic master’s programs, and 7 professional master’s programs. UESC’s strong growth in recent years has consolidated its position as a leading public higher education institution at the state, regional, and national levels.

Since the early 2000s, researchers from UESC’s Department of Exact and Technological Sciences (DCET)—which includes the areas of Computer Science, Mathematics, Engineering, Chemistry, and Physics—have conducted research in Mathematical and Computational Modeling and related interface areas. A significant milestone was the creation, in 2004, of the Laboratory of Applied and Computational Mathematics (LAMAC), through a research project funded by the Bahia Research Support Foundation (FAPESB). Since its establishment, the LAMAC team has worked diligently to consolidate and expand the laboratory’s activities.

In the years that followed, the areas of Computing, Mathematics, and Engineering at UESC made continuous efforts to attract professionals specializing in simulation and computational modeling, aiming to strengthen LAMAC’s research capabilities. Another key development in this field was the creation, in March 2005, of the Applied and Computational Mathematics Research Group (GPMAC), registered with the National Council for Scientific and Technological Development (CNPq). This group brings together researchers and students from diverse academic backgrounds, united by the use of scientific computing tools to solve problems across various areas of knowledge.

The sustained efforts of GPMAC researchers, along with the approval of numerous research projects by funding agencies, enabled the establishment of a new facility within UESC’s Center for Computational Biology and Management of Biotechnological Information (NBCGIB). The relocation and installation of LAMAC in this modern, functional, and spacious facility took place in July 2008, significantly enhancing its capacity with state-of-the-art computational resources.

Another important milestone for computational modeling research at UESC was the acquisition, in 2012, of the CACAU supercomputer (Centro de Armazenamento de Dados e Computação Avançada da UESC). This parallel machine—comprising 20 computing nodes, 160 cores, and 320 GB of RAM—was, at the time of acquisition, ranked as the most powerful computing cluster in the state of Bahia and the second largest in the Northeast of Brazil. The purchase was funded through the Research Infrastructure Program of the Brazilian Innovation Agency (FINEP). Over the years, multiple upgrades have been made to the equipment and its supporting infrastructure, including a major enhancement approved in 2018 through a competitive FINEP call, with the new system currently in the acquisition phase.

The Master’s Degree in Computational Modeling in Science and Technology emerged as a direct result of LAMAC’s consolidation and is part of a broader planning and capacity-building initiative of the DCET, launched in 2006. This initiative has led to the approval of several nationally funded projects, innovative partnerships with the private sector (particularly with companies in the information technology field), and the creation of both stricto sensu and lato sensu graduate programs.

In 2010, GPMAC faculty members recognized the need to offer students in the region the opportunity to enroll in a stricto sensu graduate program in technology, enabling them to advance their education while addressing both local and global challenges within the university setting.

The current permanent faculty of the program is composed of multidisciplinary researchers who, although all affiliated with the Department of Exact and Technological Sciences (DCET), conduct research in distinct areas, including Computational Modeling, Physics, Bioinformatics, Mathematics, Biomedical Informatics, and Engineering.

Since the program’s launch in 2013, annual admissions processes have been held, with an average intake of approximately 17 students per year. The demand for the program has been consistently high, with at least three applicants competing for each available position. As of May 2021, the program has awarded 75 master’s degrees and has 38 students currently enrolled. The PPGMC faculty remain committed to improving the program’s performance indicators, with the strategic goal of submitting a doctoral program proposal to address the region’s growing academic and research needs.

Scholarships

Acceptance by a supervisor or approval in the Selection Examination does not imply the automatic granting of a scholarship. However, the program consistently seeks to secure scholarships from funding agencies. Indeed, prior to each selection process, faculty advisors—working in collaboration with the program’s coordination and UESC’s Office of Research and Graduate Studies (PROPP)—submit applications for Demanda Social scholarships to funding agencies such as CAPES, FAPESB, and CNPq.

Regular students without employment may apply for scholarships, in accordance with the criteria established by the funding agencies and the Program’s Academic Committee.

Scholarships are awarded according to the ranking order in the selection process and the requirements set forth in the selection notice.

Master’s scholarships may be awarded for a maximum period of 24 months, and doctoral scholarships for up to 48 months.