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Job ID: 257302

INESC TEC | Research Grant (AE2025-0225)
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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RSS Feed Source: Academic Keys

Job ID: 257306

INESC TEC | Research Grant (AE2025-0223)
INESC TEC

Research Opportunities

Power Systems

Work description

Analyze the current prototype of the air quality meter. Review the electronic circuit used in the meter. Update the control code of the meter. Enhance the existing communication system. Create an intuitive dashboard for data presentation. Develop a new case for the meter.

Minimum profile required

Experience using microcontrollers such as Arduino and/or Raspberry Pi. Practical knowledge of sensors for measuring environmental variables such as temperature, humidity, gases, and particles. Experience with communication protocols. Knowledge in CAD design. Experience with 3D printing and CNC.

Preference factors

Knowledge in IoT concepts. Integration capacity of HW and SW for sensors. Experience with communication protocols like MQTT. Familiarity with development and debugging tools.

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RSS Feed Source: Academic Keys

Research Opportunities

Artificial Intelligence

Work description

1) Development of workflows and methods enabling AI testing to support the safe operation of local energy communities and microgrids.

2) Develop methodologies for assessing the robustness and safety of AI-based decision and control systems, considering risk assessment aligned with the EU AI Act.

3) Validate the developed methodologies on real data and with real consumers/prosumers.

4) Dissemination of the work in international journals and/or conferences

Minimum profile required

Previous academic background in or electrical engineering or applied mathematics or computer science or informatics or similar.

Preference factors

Past experience (or academic background) with machine learning. Academic background in energy systems. Programming knowledge in Python.

Maintenance stipend: € 1851.00, 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

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RSS Feed Source: Academic Keys

Job ID: 257304

INESC TEC | Research Grant (AE2025-0219)
INESC TEC

Research Opportunities

Power Systems

Work description

Definition of requirements to enable the participation of B2B and B2C clients in the aggregation case study, as well as flexible resources. Storage of data used by the EMS tool in a database. Develop algorithms to produce graphical results of case study simulations with data from living lab clients. Analyze optimized operation data from flexible resources (batteries, photovoltaic generation and heat pumps) with a view to calculating performance indicators defined in the project. Reports with case study simulations with data from living lab clients. Write the exchange activity report.

Academic Qualifications

Electrical engineering, computer engineering or related field.

Minimum profile required

Student of electrical engineering or computer science or related

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