INESC TEC is accepting applications to award 1 Research Grant for MSC or Degree holders - IGNIT - SYSTEM (AE2026-0335)

Inesc Tec; Portugal; On-site; EUR 12,000 - 15,000; Full time

Benefits offered by this job

Health insurance

Job summary

A INESC TEC em Porto abre uma bolsa de investigação BI para o projecto IGNIT. O bolseiro trabalhará em métricas de qualidade, integração de dados e modelos de machine learning para estimar causas de ignição e tipos com base em dados espaciais.

São requisitos licenciatura e mestrado em áreas relacionadas, com preferência para quem já está inscrito num doutoramento (PRODEGI ou PDEPP) e experiência com Python e R em GIS. A bolsa oferece seguro de saúde e possibilidade de renovação.

Qualifications

• Bacharelado e Mestrado em Engenharia Industrial e Gestão ou área relacionada.
• A bolsa depende de matrícula em ciclo de estudo ou cursos de não licenciado.
• Desejável experiência com R em análises GIS e Spatial Analysis Tools (QGIS, sf, Terra).
• Candidatos com motivação para desenvolver a tese de doutoramento serão privilegiados.

Responsibilities

• Adaptar métricas padronizadas e quantitativas para quantificar a qualidade de registos de dados de causas de incêndio florestal.
• Avaliar a qualidade da classificação de causas em entradas novas.
• Enriquecer o conjunto de dados de causas no SGIF integrando dados antropológicos e sociais de outras fontes.
• Utilizar o conjunto de dados existente para prever causas de ignição não resolvidas com métodos de machine learning.
• Aplicar análises espaciais para prever tipos de ignição com base em padrões espaciais tomados de um ambiente GIS.

Skills

Python programing

R em GIS

Motivação para tese de doutoramento

Education

Bacharelado e Mestrado em Engenharia Industrial e Gestão ou área relacionada

PhD student (PRODEGI ou PDEPP)

Tools

QGIS

R/RStudio

Job description

Organisation/Company INESC TEC Research Field Computer science » Modelling tools Mathematics » Applied mathematics Researcher Profile First Stage Researcher (R1) Application Deadline 11 Nov 2026 - 23:59 (UTC) Country Portugal Type of Contract Temporary Job Status Full-time Hours Per Week 36 Offer Starting Date 9 Dec 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number AE2026-0335 Is the Job related to staff position within a Research Infrastructure? No

CALL FOR GRANT APPLICATIONS (AE2026-0335)

INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope of the within the scope of the project IGNIT with reference 15418 (COMPETE2030-FEDER-00910000) co-funded by the ERDF - European Regional Development Fund through Innovation and Digital Transition Program - COMPETE 2030 under the scope of Portugal 2030.

1. GRANT DESCRIPTION

Type of grant: Research Grant (BI)

General scientific area: COMPUTER SCIENCE,MATHEMATICS

Scientific subarea: Applied mathematics,Modelling tools

Grant duration: 6 months, starting on 2026-12-09 , with the possibility of being renewed until the end of the project.

Workplace: INESC TEC, Porto, Portugal

Maintenance stipend: 1090.98 ou 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.

The grant holder will benefit from health insurance, supported by INESC TEC.

2. OBJECTIVES

As part of the IGNIT project, the research fellow will adapt metrics to characterize wildfire ignition causes, assess the quality of SGIF records, enrich these data with social, anthropological, economic and territorial information from other databases, and develop machine learning models to estimate the causes of ignitions that were not investigated or whose investigation was inconclusive, as well as to predict ignition types based on spatial patterns and socio-territorial factors.

3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING

• Adapt standardized and quantitative metrics to quantify forest fire-ignition causes data records quality;
• Assess the quality of cause classification in fresh entries;
• Enhance the existing causes dataset in SGIF by integrating anthropological and social data derived from other sources (e.g. National Statistics Institute, PORDATA, fieldwork, and others sources);
• Use the existing causes dataset in SGIF to predict ignition causes investigated by traditional methods without success, by using machine learning methods;
• Use the existing causes dataset in SGIF to predict ignition causes not investigated, by using machine learning methods;
• Use analytics and machine learning methods to predict ignition types based on the results of a spatial analysis previously performed in a GIS environment.

4. REQUIRED PROFILE

Admission requirements

• Bachelor's and Master's degree in Industrial Engineering and Management or related field.
• The awarding of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions.

Preference factors

• Python programming;
• Experience and domain in the use of R in analyses involving GIS, Cartographic and Spatial Analysis Tools (QGIS, sf, Terra);
• Motivation for personal and professional development, in addition to the inclusion of the theme of this Grant in the objectives of the doctoral thesis.

Minimum requirements

• PhD student (PRODEGI or PDEPP);
• Experience in the development of R scripts for data manipulation and preparation, and algorithms in applications within the scope of Integrated Rural Fire Management through R&D projects, company internship, or professional career;
• Experience with R/RStudio.

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: António Miguel Gomes
• Full member: Fantina Maria Santos Tedim
• Full member: Abílio Pereira Pacheco
• Substitute member: Jorge Daniel Teixeira

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.

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.

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 https://files.dre.pt/2s/2019/12/241000000/0009100105.pdfFCT Grants Regulation in force.

For more information, please check the Regulations for Grants of INESC TEC and relevant annexes at www.inesctec.pt/bolsas

Academic qualifications: Bachelor's and Master's degree in Industrial Engineering and Management or related field. Minimum profile: PhD student (PRODEGI or PDEPP); Experience in the development of R scripts for data manipulation and preparation, and algorithms in applications within the scope of Integrated Rural Fire Management through R&D projects, company internship, or professional career; Experience with R/RStudio.

Preference factors: Python programming; Experience and domain in the use of R in analyses involving GIS, Cartographic and Spatial Analysis Tools (QGIS, sf, Terra); Motivation for personal and professional development, in addition to the inclusion of the theme of this Grant in the objectives of the doctoral thesis.

Additional Information

Maintenance stipend: 1090.98 ou 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_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.

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.