Research Grant (BI) - Industrial Engineering

Offer Description

Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0227.pdf

CALL FOR GRANT APPLICATIONS (AE2026-0227)

INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope of the within the scope of the project LOGIX, with reference 26049 (COMPETE2030-FEDER-03240400) 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 2026-10-26, with the possibility of being renewed until the end of the project.

Scientific advisor: António Galrão Ramos

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:

• Develop artificial intelligence and metaheuristic algorithms for automatic product recognition and picking in warehouse environments;
• Design and implement bin-picking systems supported by computer vision (product detection and localization);
• Develop a mosaic generation ("product-to-bin") system for internal packing planning of shipping boxes containing mixed-SKU products, maximizing volumetric usage and reducing the transport of empty space;
• Integrate collision detection and avoidance mechanisms between the robot, products and boxes, ensuring product integrity during picking and packing;
• Test, validate and tune the developed solutions in a laboratory environment and, at a later stage, in a real operational context (industrial pilot);
• Contribute to the project's scientific output (technical reports and possible publications).

3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING:

• Develop artificial intelligence and metaheuristic algorithms for automatic product recognition and picking in warehouse environments;
• Design and implement bin-picking systems supported by computer vision (product detection and localization);
• Develop a mosaic generation ("product-to-bin") system for internal packing planning of shipping boxes containing mixed-SKU products, maximizing volumetric usage and reducing the transport of empty space;
• Integrate collision detection and avoidance mechanisms between the robot, products and boxes, ensuring product integrity during picking and packing;
• Test, validate and tune the developed solutions in a laboratory environment and, at a later stage, in a real operational context (industrial pilot);
• Contribute to the project's scientific output (technical reports and possible publications).

4. REQUIRED PROFILE:

Admission requirements:

Master in Industrial Engineering and Management, Informatics Engineering.

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 of Machine Learning and computer vision (e.g. OpenCV, PyTorch/TensorFlow).;
• Knowledge of metaheuristics applied to combinatorial optimization problems.;
• Knowledge of version control tools (Git).;
• Knowledge of combinatorial optimisation solvers.;
• Experience in R&D projects with companies.

Minimum requirements:

• Experience in the following skill(s):
• Programming in Python and/or C++;
• Analysis and development of optimization models (metaheuristics and/or mathematical programming);
• Experience in using the HiGHSsolver
• Ability to work in a group, high autonomy, and organization.
• Experience in 3D cutting and packing problems.
• Advanced knowledge of English (spoken and written).
• Advanced knowledge of Portuguese (spoken and written).

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, 35), Scientific Publications (PC, 25), Experience (EX, 15) and Motivation Letter (CM, 25).

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 (70) and EI (30).

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: António Galrão Ramos

Full member: Fábio Silva Moreira

Full member: Pedro Filipe Rocha

Substitute member: Farzam Salimi

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:

1. Motivation letter;
2. Curriculum Vitae (must include the list of previous fellowships, their type, beginning and end dates, funding entities and host institutions);
3. Certificate or diploma degree;
4. 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.
5. Signed declaration stating the infringement of the grant holder's duties (article 14, no. 4)
6. 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.
7. 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 2026-09-24 to 2026-10-08

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/AE2026-0227

Requirements

• Research Field: Engineering
• Education Level: Master Degree or equivalent

Specific Requirements

Academic qualifications: Master in Industrial Engineering and Management, Informatics Engineering.

Minimum profile: - Experience in the following skill(s):, - Programming in Python and/or C++;, - Analysis and development of optimization models (metaheuristics and/or mathematical programming);, - Experience in using the HiGHSsolver, - Ability to work in a group, high autonomy, and organization., - Experience in 3D cutting and packing problems., - Advanced knowledge of English (spoken and written)., - Advanced knowledge of Portuguese (spoken and written).

Preference factors: - Knowledge of Machine Learning and computer vision (e.g. OpenCV, PyTorch/TensorFlow).; - Knowledge of metaheuristics applied to combinatorial optimization problems.; - Knowledge of version control tools (Git).; - Knowledge of combinatorial optimisation solvers.; - Experience in R&D projects with companies.

• 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, 35), Scientific Publications (PC, 25), Experience (EX, 15) and Motivation Letter (CM, 25).

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 (70) and EI (30).

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: António Galrão Ramos

Full member: Fábio Silva Moreira

Full member: Pedro Filipe Rocha

Substitute member: Farzam Salimi

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/AE2026-0227

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