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Job ID: 255013

INESC TEC | Research Grant (AE2025-0148)
INESC TEC

Research Opportunities

Efficiency and Effectivess of educational systems

Work description

Contextualisation of the education landscape in the European Union. Literature review, as thorough as possible. Identification of the knowledge gap that the dissertation aims to cover. Collection and processing of data, including the contextual variables relevant to the problem. Implementation of Robust Conditional Approaches, based on Data Envelopment Analysis (DEA) or Benefit of the Doubt (BoD) models. Implementation of Goal Programming approaches. Analysis of the results. Discussion of the results.

Academic Qualifications

Master Degree in Industrial Engineering and Management.

Minimum profile required

Average grade of 18 in the Master Degree in Industrial Engineering and Management.

Preference factors

Good knowledge of the English language. The

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RSS Feed Source: Academic Keys

Research Opportunities

Artificial intelligence and remote observation for IoT and Robotics

Work description

The TRIBE LAB Laboratory – Robotics and IoT for precision agriculture and forestry has been working on robotic and IoT technology that needs to be integrated with a decision support system, to increase its autonomy and impact. In this context, the aim is to explore new projects, publications and concepts integrating Artificial Intelligence and data provided by satellites, drones, robots and IoT to obtain prescription, productivity and action maps, which can support the farmer in his decision-making, as well how to automate the connection between the decision support system and robots.

Academic Qualifications

PhD in agricultural production chains, computer sciences, engineering and similar.

Minimum profile required

Experience with geographic information systems. More than 10 scientific publications in indexed journals. Proven experience in using machine learning techniques using Python.

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Research Opportunities

Operations Research

Work description

Development of a solution method destined to solving a network design problem within the scope of the insect-based products supply chain. Analysis of the obtained results based on sensitivity analyses.

Academic Qualifications

Master’s Degree in Engineering and Industrial Management, or similar.

Minimum profile required

Proficiency in English. Knowledge in linear and integer programming. Programming skills in Python and C++. Previous contact with the development of approximate solution methods for optimization problems.

Preference factors

Previous experience in decision methods applied to supply chain planning.

Maintenance stipend: € 1309,64, according to the table of monthly maintenance stipend for FCT grants , 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

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