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Research Opportunities

Engineering

Work description

• Contribute to the identification of key gaps in the organisation of physical assets and laboratory testing platforms within the x-Energy laboratory.

• Assist in identifying processes for organising physical assets and laboratory testing platforms that are tailored to the specific needs of the x-Energy laboratory.

• Support the implementation of a management platform based on commercial or open-source software (such as ERPNext or Odoo Community), along with maintenance plans for the equipment and infrastructure of the x-Energy laboratory.

• Participate in internal training activities focused on best practices in laboratory management and the utilisation of adopted digital tools.

Academic Qualifications

Be enrolled in a higher education course in Management, Industrial Engineering, Electrical Engineering, or related fields;

Minimum profile required

• Ability to use basic computer tools (spreadsheets, documents, web systems).

• Communication and organizational skills.

Preference

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Job ID: 259622

INESC TEC | Research Grant (AE2025-0261)
INESC TEC

Research Opportunities

Computer Science

Work description

Development of model/process chains that enable AI-based assistants to support human operators’ decisions in power systems under model risk and uncertainty, and considering joint human-AI learning. Develop methodologies to assess the robustness and safety of human decisions assisted by AI, hybrid co-learning between AI and humans, and fully autonomous AI, considering risk assessment aligned with the EU AI Act, as well as reliability and robustness quantified through the provision of guidelines on how to create and use “adversarial” datasets. Validate the developed methodologies using real data and simulators. Dissemination of the work in national and/or international journals and conferences.

Academic Qualifications

Degree in Computer Science, Informatics of similar area

Minimum profile

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Research Opportunities

Business systems engineering; Optimisation of logistics processes

Work description

Design and development of optimisation models and algorithms for planning and scheduling problems in container terminal logistics operations. Evaluating the approaches developed and analysing results (KPIs). Writing scientific articles and the grant activity report.

Academic Qualifications

Master in Industrial Engineering and Management.

Minimum profile required

Master’s in Industrial Engineering and Management. Knowledge of English and Portuguese.

Preference factors

Knowledge of Operational Research and Operations Management. Experience in optimisation and programming in Python, Java or similar. Ability to work autonomously and as part of a team.

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

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