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Job ID: 261151

INESC TEC | Research Grant (AE2025-0361)
INESCTEC

Research Opportunities

Industrial Robotics

Work description

Develop a digital twin environment for robotic cells. Integrate AR devices with simulators using open-source standards. Acquire task execution data using AR devices. Adapt robot movements based on the acquired data. Test and validate the system developed at iiLab/INESC TEC.

Academic Qualifications

Degree in Electrical and Computer Engineering.

Minimum profile required

Enrollment in a Master’s degree in Electrical and Computer Engineering. Proven experience in R&D projects. Knowledge of Blender and NVIDIA USD Composer. Experience in C/C++ programming. Experience with Artificial Intelligence frameworks.

Preference factors

The candidate must have knowledge of robotics and programming. Extracurricular activities, such as participation in competitions or demonstrations at the National Robotics Festival or similar

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RSS Feed Source: Academic Keys

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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Scientists have developed a lightning-fast AI tool called HEAT-ML that can spot hidden “safe zones” inside a fusion reactor where parts are protected from blistering plasma heat. Finding these areas, known as magnetic shadows, is key to keeping reactors running safely and moving fusion energy closer to reality.

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A workforce fluent in AI techniques will be essential to ensure U.S. leadership in artificial intelligence continues. Jeremy Waisome, an assistant professor at the University of Florida, discusses the Shark AI project, which has introduced artificial intelligence and machine learning techniques to thousands of middle school students.

Listen to NSF Discovery Files wherever you get your podcasts.

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