INESC TEC is accepting applications to award 1 Research Grant for MSC holders - CARE-IN-HEALTH - CBER (AE2026-0226)

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Testo originale dell'annuncio (in inglese)

Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0226.pdf CALL FOR GRANT APPLICATIONS (AE2026-0226) INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope of the on the scope CARE-IN-HEALTH with reference 101095413 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: 12 months, starting on 2026-09-01 , with the possibility of being renewed until the end of the project. 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: Creation of a biological signal analysis and classification pipeline for differentiation between different class types. Assembly of a data acquisition bench. Documentation of all work performed and the use of the bench systems. Publication of an article in a journal within the scope of this work. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Application of signal processing techniques for feature extraction in biosignals. Application of machine learning techniques for classification of different classes using the extracted features. Assembly, documentation, testing, and use of an innovative biosensing system for data collection. Active participation in the writing of scientific articles within the scope of this work. 4. REQUIRED PROFILE: Admission requirements: Master's degree in Biomedical Engineering, Electrical Engineering, 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: Knowledge in the use of machine learning techniques for clinical data analysis. Minimum requirements: Prior knowledge of clinical data analysis and processing. Prior experience in clinical settings involving data collection and organization. 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, 30), Scientific Publications (PC, 10), Experience (EX, 30) and Motivation Letter (CM, 30). 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 weighted average of AC (60) and EI (40). DISABILITY INCENTIVE Candidates who present a degree of disability equal to or greater than 90% will benefit from an incentive (20) in the score of the CV Assessment. Candidates who present a degree of disability equal to or greater than 60% and less than 90% will also benefit from an incentive (10) in the score of the Annuncio in ingles