Offer Description
CALL FOR GRANT APPLICATIONS (AE[contact details available in the full listing])
INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope of the Multiannual Funding of R&D Units [contact details available in the full listing], 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 Grant (BI)
General scientific area: ENGINEERING
Scientific subarea: Industrial engineering
Grant duration: 12 months, starting on 2026-09-22 with the possibility of being renewed for a maximum term of two years, in the cases of students enrolled in a master's degree.
Scientific advisor: Vera Miguéis
Workplace: INESC TEC, Porto, Portugal
Maintenance stipend: 1090.98, according to the table of monthly maintenance stipend for FCT grants (link), 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"
The grant holder will benefit from health insurance, supported by INESC TEC.
2. OBJECTIVES:
The work aims to develop and integrate advanced artificial intelligence solutions into a platform to support the estimation of time, effort, and service planning.; The fellow will contribute to the research, development, and validation of artificial intelligence and machine learning models, exploring different algorithmic approaches, training and evaluation methodologies, and scientific validation mechanisms, based on real operational data.
3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING:
- Study the state of the art and different approaches to artificial intelligence and machine learning for estimating effort, duration, and service planning;
- Analyze and characterize the data made available within the scope of the project and identify relevant variables for modeling;
- Develop, train, and compare different machine learning models;
- Define methodologies and metrics for evaluating the predictive performance, robustness, and generalization ability of the models;
- Conduct iterative cycles of testing, validation, and fine-tuning of the developed models;
- Contribute to the integration and technical validation of the models in a controlled operational context ;
- Document methodologies, experimental results, and technical recommendations;
- Contribute to the technical and scientific dissemination of the project’s non-confidential results.
4. REQUIRED PROFILE:
Admission requirements: Bachelor’s degree in industrial engineering and management. The awarding of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions.
Preference factors: Good command of English.; Experience in science communication.; Good knowledge of Python programming.
Minimum requirements: Final bachelors's degree average equal to or higher than 18 points. Good knowledge of Data Science and Deep Learning. Previous experience in research projects.
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, 10), Experience (EX, 30) and Motivation Letter (CM, 10). 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: Vera Miguéis; Full member: António Henrique Almeida; Full member: Jorge Daniel Teixeira; Substitute member: Beatriz Brito Oliveira
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 2026-08-21 to 2026-09-03
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/AE2026-0256
Requirements
Research Field: Engineering
Education Level: Bachelor Degree or equivalent
Specific Requirements: Academic qualifications: Bachelor’s degree in industrial engineering and management. Minimum profile: Final bachelors's degree average equal to or higher than 18 points., Good knowledge of Data Science and Deep Learning., Previous experience in research projects. Preference factors: Good command of English.; Experience in science communication.; Good knowledge of Python programming.
Research Field: Engineering » Industrial engineering
Years of Research Experience: None
Additional Information
Benefits: Maintenance stipend: 1090.98 euros, according to the table of monthly maintenance stipend for FCT grants (link), 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, 10), Experience (EX, 30) and Motivation Letter (CM, 10). 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: Vera Miguéis; Full member: António Henrique Almeida; Full member: Jorge Daniel Teixeira; Substitute member: Beatriz Brito Oliveira 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/AE2026-0256
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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