Job Information
Organisation/Company: INESC TEC
Research Field: Engineering » Industrial engineering
Researcher Profile: First Stage Researcher (R1)
Application Deadline: 19 Aug 2026 - 23:59 (UTC)
Country: Portugal
Type of Contract: Temporary
Job Status: Full-time
Hours Per Week: 36
Offer Starting Date: 14 Sep 2026
Is the job funded through the EU Research Framework Programme?: Not funded by a EU programme
Reference Number: AE2026-0246
Is the Job related to staff position within a Research Infrastructure?: No
Offer Description
Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0246.pdf
CALL FOR GRANT APPLICATIONS (AE2026-0246)
INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope of the project FSAI4WIND, with reference COMPETE2030-FEDER-03274700 - 26277 Co-funded by ERDF - European Regional Development Fund through the Innovation and Digital Transition Thematic Programme (COMPETE 2030) within the scope of Portugal 2030.
1. GRANT DESCRIPTION
Type of grant: Research Grant (BI)
General scientific area: ENGINEERING
Scientific subarea: Industrial engineering
Grant duration: 12 months, starting on 2026-09-14 , with the possibility of being renewed until the end of the project.
Scientific advisor: Flávia Barbosa
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_atualizacao-2024.pdf), 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:
- Characterize the asset system under study, including the identification of the main critical components, the modelling of nominal operational behavior and admissible system variability, as well as the available sources of operational and condition data, leveraging physical AI techniques to model the behavior of the system components.
- Define alarmist strategies that enable the prioritization of decision-making based on risk levels, in a clear manner for the user, using natural language and supported by model explainability mechanisms.
- Develop data-driven and/or causal model-based approaches for the identification of root causes leading to atypical asset degradation, considering charging systems as complex and multidisciplinary systems, and using this information to support continuous product improvement.
- Define a set of performance indicators to support asset management, including reliability, maintenance, and cost metrics, ensuring their consistent use in the evaluation of alternatives.
3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING:
The work is framed within the AI4WIND project and focuses on asset management associated with wind turbine blades, which are characterised by demanding operating conditions and high criticality in terms of availability and safety.
The central objective is to develop a platform that helps reduce operation and maintenance costs and decrease unplanned downtime in wind farms. The project is also expected to support the extension of the useful life of wind energy assets, as well as a potential increase in energy production, the creation of new business models, and the strengthening of the export and internationalisation potential of the technologies developed.
The work integrates the analysis of failure modes and structural degradation in wind turbine blades, the use of monitoring data from optical sensors, SCADA systems, and inspection reports, as well as the development of artificial intelligence models for early damage detection, prediction of degradation evolution, and estimation of the remaining useful life of the assets. Additionally, it includes the development of edge processing and edge–cloud communication methodologies, enabling complex data on deformation, loads, and structural condition to be transformed into reliable and actionable operational information.
In particular, the aim is to assess the impact of these solutions on the overall performance of wind energy assets, including availability, annual energy production, operation and maintenance costs, risk of unplanned failures, and extension of blade lifetime. The project will thus contribute to the development of advanced capabilities in condition monitoring, predictive maintenance, decision support, and asset management in the context of renewable energy systems.
4. REQUIRED PROFILE:
Admission requirements:
- Bachelor Degree in Industrial Engineering and Management or similar area.
- The awarding of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions.
Preference factors:
- Experience in developing data-driven models for decision support, including the analysis of real-world data, modelling, and solution evaluation.
- Experience with quantitative methods applied to engineering problems (e.g., optimisation, simulation, statistical analysis, or applied machine learning).
Minimum requirements:
- Average grade of 18 in the Master Degree in Industrial Engineering and Management.
- Proficiency in Portuguese and English.
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, 50), Scientific Publications (PC, 0), Experience (EX, 20) 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 CV Assessment.
Said score may, in these cases, exceed 100 points.
Candidates must demonstrate the degree of disability during the application, namely through the submission of the Multi-Purpose Medical Certificate of Disability, issued in accordance with Decree-Law no. 202/96, of October 23 - currently in effect.
The Selection Jury is composed of the following members:
- President of the Jury: Flávia Barbosa
- Full member: António Henrique Almeida
- Full member: Hermilio Vilarinho
- Substitute member: Luís Guimarães
Release of results and prior hearing: the results of the selection process, as well as the terms and procedures for prior hearing, will be released to the applicants by email, under the terms referred to in Article 13 of the Regulations for Studentships and Fellowships of INESC TEC.
6. FORMALISATION OF APPLICATIONS:
Application Documents:
- Motivation letter;
- Curriculum Vitae (must include the list of previous fellowships, their type, beginning and end dates, funding entities and host institutions);
- Certificate or diploma degree;
- Proof of enrollment in a degree awarding study cycle or in a non degree awarding Higher Education program. - The proof of enrollment may be presented just during the grant hiring stage.
- Signed declaration stating the infringement of the grant holder's duties (article 14, no. 4)
- Documental evidence to support the country of residence, residence permit or other legally equivalent document, in cases where the applicant is a foreigner or non-resident in Portugal - valid until the beginning of the grant.
- Other supporting documents relevant to the final assessment.
Failure to deliver the required documents within the 90-day period after the date of the notice of the conditional awarding of the grant implies its cancellation.
Application period: From 2026-08-06 to 2026-08-19
Submission of applications: the application will be formalised by submitting the form available in the Work With Us section of INESC TEC website.
7. BINDING LEGISLATION AND REGULATION
The hiring process shall comply with the current legislation regarding the Research Grant Holder Statute, approved by Law no. 40/2004 of August 18, in its current wording, as well as by the Regulations for Grants of INESC TEC and for FCT Grants Regulation in force.
For more information, please check the Regulations for Grants of INESC TEC and relevant annexes at www.inesctec.pt/bolsas
Where to apply
Website: https://www.inesctec.pt/en/opportunity/AE2026-0246
Requirements
Research Field: Engineering
Education Level: Master Degree or equivalent
Specific Requirements
Academic qualifications: Bachelor Degree in Industrial Engineering and Management or similar area.
Minimum profile: Average grade of 18 in the Master Degree in Industrial Engineering and Management., Proficiency in Portuguese and English.
Preference factors: Experience in developing data-driven models for decision support, including the analysis of real-world data, modelling, and solution evaluation.; Experience with quantitative methods applied to engineering problems (e.g., optimisation, simulation, statistical analysis, or applied machine learning).
Research Field: Engineering » Industrial engineering
Years of Research Experience: None
Additional Information
Benefits
Maintenance stipend: 1359.64 euros, according to the table of monthly maintenance stipend for FCT grants (https://www.fct.pt/wp-content/uploads/2024/02/Tabela-de-Valores-SMM_atualizacao-2024.pdf), 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.
Costs attributable to INESC TEC may include registration, enrolment or tuition fee stipend, either directly or through reimbursement, during the grant duration.
The grant holder will benefit from health insurance, supported by INESC TEC.
Selection process
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, 50), Scientific Publications (PC, 0), Experience (EX, 20) 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 CV Assessment.
Said score may, in these cases, exceed 100 points.
Candidates must demonstrate the degree of disability during the application, namely through the submission of the Multi-Purpose Medical Certificate of Disability, issued in accordance with Decree-Law no. 202/96, of October 23 - currently in effect.
The Selection Jury is composed of the following members:
- President of the Jury: Flávia Barbosa
- Full member: António Henrique Almeida
- Full member: Hermilio Vilarinho
- Substitute member: Luís Guimarães
Release of results and prior hearing: the results of the selection process, as well as the terms and procedures for prior hearing, will be released to the applicants by email, under the terms referred to in Article 13 of the Regulations for Studentships and Fellowships of INESC TEC.
Website for additional job details
https://www.inesctec.pt/en/opportunity/AE2026-0246
Work Location(s)
Number of offers available: 1
Company/Institute: INESC TEC
Country: Portugal
City: Porto
Postal Code: 4200-465
Street: Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias
Contact
City: Porto
Website: http://www.inesctec.pt
Street: Campus da FEUP - Rua Dr. Roberto Frias
Postal Code: 4200-465 Porto
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