INESC TEC is accepting applications to award 1 Research Grant for MSC holders - AI4REALNET - CBER (AE2026-0222)

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Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0222.pdf CALL FOR GRANT APPLICATIONS (AE2026-0222) INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope of the on the scope AI4REALNET with reference 101119527 funded by the European Commission under the Horizon Europe program for the period 2021-2027. 1. GRANT DESCRIPTION Type of grant: Research Grant (BI) General scientific area: COMPUTER SCIENCE Scientific subarea: Computer Systems Grant duration: 7 months, starting on 2026-09-01 . Scientific advisor: Duarte Filipe Dias Workplace: INESC TEC, Porto, Portugal Maintenance stipend: 1359.64, 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 and improvement of developed algorithms - Automation of the model customization process by conducting laboratory tests. - Improvement of the data workflow for real-time processing and sharing. - Data collection in experimental and real-world environments - Data analysis and correlation - Management of the code repository and the collected database - Participation in project meetings - Writing scientific articles. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Participation in a European project (AI4REALNET) that aims to integrate human contextual information into the interaction between an operator and the system that provides AI-based suggestions. The work will consist in the improvement and evolution of previously developed models, as well as interacting with project partners to integrate algorithms and conduct field studies. Subsequent data analysis, as well as writing articles and possible participation in conferences, will also be part of the activities 4. REQUIRED PROFILE: Admission requirements: Master's degree in biomedical engineering, bioengineering, electrical and computer engineering, computer engineering, or other similar 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: Prior knowledge of psychophysiological variables. Previous work with ECG signals and field data collection using wearable devices. Minimum requirements: Advanced knowledge of machine learning models and Python tools for signal processing and machine learning. General knowledge of system architecture and APIs. Previous knowledge of physiological signal processing. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC), based on the criteria referred to in Article 12 of the Regulations for Grants of INESC TEC, while the second phase comprehends the Individual Interview (EI). All factors are evaluated on a scale of 0 to 100, taking into account the applicants' merit, suitability and conformity with the preference factors. The weight of the AC factors are as follows: Academic Qualifications (FA, 25), Scientific Publications (PC, 20), Experience (EX, 35) and Motivation Letter (CM, 20). Candidates who score less than 50 points in the AC average will be considered excluded on absolute merit. The top five candidates approved on absolute merit will be qualified for the individual interview. The Final Grade (CF) is obtained by the w