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Job ID: 261149

INESC TEC | Researcher (AE2025-0358)
INESC TEC

Research Opportunities

Computer Science

Work description

The work plan falls within the scope of the project supporting the European supercomputing infrastructure, with the participation of INESCTEC. The main focus is work plan is to support users of supercomputing infrastructures, especially in the optimization and profiling of scientific applications in pre-exascale and exascale environments.

Academic Qualifications

National, foreigner and stateless candidates holding a master degree in Electrical and Computers , Computer Science, Physics, or related scientific area, and holders of a scientific and professional curriculum showing a relevant profile for the activity to be developed can apply for the tender.

Minimum profile required

Demonstrated competence and experience in the development of applications in C++, C, Fortran, and Python. Experience in

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RSS Feed Source: Academic Keys

Job ID: 261150

INESC TEC | Researcher (AE2025-0359)
INESCTEC

Research Opportunities

Computer Science

Work description

The work plan addresses the needs in current Research and Development (R&D) projects in INESC TEC to build software prototypes with high assurance and interoperability guarantees, that can leverage from the ecosystem of cloud service providers. The specific objectives are detailed in the objectives section.

Academic Qualifications

Degree in Informatics Engineering, Computer Science or alike.

Minimum profile required

Knowledge and experience in the development of Java applications. Knowledge and experience with orchestration tools in cloud providers. Knowledge and experience with relational and non-relational database management systems. Knowledge and experience with the following virtualization/orchestration tools: Ansible, Docker, Kubernetes. Knowledge and experience with Linux operating systems. Language skills (written and spoken) for Portuguese and English.

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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.

Academic Qualifications

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

Minimum profile required

Experience (or academic background) in machine learning. Knowledge of electrical power systems. Experience and orientation towards research. Previous experience (or academic background) in data analysis.

Preference factors

Programming knowledge in Python.

Maintenance stipend: € 651.12, according to the table of monthly maintenance stipend for FCT

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Research Opportunities

R&D+i

Work description

The candidate will support the management of the marine area laboratory infrastructure at INESC TEC, collaborating in the maintenance, repair, and technical support of equipment, as well as in the design and manufacturing of new mechanical components.

They will work under the guidance of more experienced technicians and will be involved in optimising the machining process of parts for robots across different platforms.

Academic Qualifications

The candidate must have at least a secondary school (12th year) education.

Minimum profile required

Professional experience with automated systems, robotic manufacturing cells, and computer-assisted centralised industrial process control systems.

Preference factors

Technical-Vocational Course, preferably in the areas of electrical engineering, industrial maintenance, mechatronics, or similar. A minimum of 1 to 3 years of professional experience in technical roles related to maintenance or electromechanics. Internships in relevant environments are

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