INESC TEC is accepting applications to award 1 Scientific Research Grant - Plurianual_25-29 - CRACS (AE2026-0234)

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Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0234.pdf CALL FOR GRANT APPLICATIONS (AE2026-0234) INESC TEC is now accepting grant applications to award 1 Research Initiation Grant (BII) within the scope of the Multiannual Funding of R&D Units 2025-2029, with the reference UID/50014/2025, Funded by national funds through the Portuguese Foundation for Science and Technology (FCT), I.P. 1. GRANT DESCRIPTION Type of grant: Research Initiation Grant (BII) General scientific area: COMPUTER SCIENCE Scientific subarea: Programming,Informatics Grant duration: 3 months, starting on 2026-10-01 , with the possibility of being renewed for a maximum term of one year. Scientific advisor: Pedro Manuel Ribeiro Workplace: INESC TEC, Porto, Portugal Maintenance stipend: 701.12, according to the table of monthly maintenance stipend for FCT grants ( https://www.fct.pt/wp-content/uploads/2024/02/Tabela-de-Valores-SMM_atu… ), paid via bank transfer. Grant holders may be awarded potential supplements, according to a quarterly evaluation process (Articles 19, 21 and 22 of the Regulations for Grants of INESC TEC and Annex II), up to a maximum limit of 50 of the monthly maintenance stipend. INESC TEC supports costs with registration, enrolment or tuition fees, during the grant duration, under the terms established in the internal document: "Payment of Tuition fees to grant holders" ( https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Study the main exact subgraph counting algorithms identified in the survey (e.g., ESU/FANMOD, Kavosh, GTrie, FaSE, ORCA, PGD, ESCAPE, ACC-MOTIF), with special attention to publicly available implementations; - Install, configure, and validate these implementations, ensuring that they produce correct and mutually comparable results; - Build a benchmark dataset of real and synthetic networks of varying dimensions and densities; - Conduct a systematic experimental comparison of the selected algorithms, evaluating runtime, memory usage, and scalability (as a function of network size and the size k of the subgraphs); - Research the most recent developments (post-2019/2021) in the field to identify any new algorithms or relevant implementations not covered in the original survey; - Document the entire process (scripts, configuration, results) in a reproducible manner in a public repository; - Prepare a final report presenting the results obtained and a comparative discussion of the algorithms studied. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Subgraph counting is a fundamental task in network analysis, serving as the basis for widely used methodologies such as network motifs and graphlets, which are applied in fields as diverse as biology, social networks, and transportation networks. It is, however, a computationally very demanding problem. Over the past two decades, numerous exact algorithms have been proposed to solve it, each with different strategies, limitations, and performance characteristics.; This work will take as its starting point the survey “A Survey on Subgraph Counting: Concepts, Algorithms, and Applications to Network Motifs and Graphlets” (Ribeiro et al., ACM Computing Surveys, 2021), which provides a structured taxonomy of exact, approximate, and parallel algorithms, indicating which ones have publicly available implementations. 4. REQUIRED PROFILE: Admission requirements: Undergraduate or graduate students in computer science, informatics, or related fields. The awarding of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - Previous experience with C/C++ programming (many of the implementations to be compared are written in these languages); - Knowledge of graph theory and/or complex network analysis; - Experience with scripting for automating experiments (e.g., Bash, Python)