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School of Electrical and Electronic Engineering is one of the founding Schools of the Nanyang Technological University. Built on a culture of excellence, the School is renowned for its high academic standards and research. With over 3,000 undergraduate students and 2,000 graduate students it is one of the largest EEE schools in the world and ranks 4th in the field of Electrical & Electronic Engineering in the 2025 QS World University Rankings by Subjects.

Today, the School has become one of the world’s largest engineering schools that nurture competent engineers and researchers. Each year, the School graduates over a thousand students who are ready to take on great ambitions and challenges.

For more details, please view: https://www.ntu.edu.sg/eee

We are hiring a Research Associate/Research Fellow in Information Engineering and Media to develop Machine Learning and AI algorithms for real-world and media-related applications. The Research Associate/Research

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RSS Feed Source: Academic Keys

Job ID: 256554

INESC TEC | Research Initiation Grant (AE2025-0193)
INESC TEC

Research Opportunities

Industrial Robotics

Work description

Prepare a comprehensive literature review on robotic grasping and binpicking techniques with exclusive use of machine learning and intelligence artificial. Develop a grasping pipeline integrated with ROS, aimed at tasks of bin-picking with support for AI algorithms. Acquire practical skills in using the Omniverse simulator, focusing on simulation of robots and evaluation of grasping algorithms. Perform experimental tests in a simulated environment and with a physical robot, whenever possible. Write the scholarship activity report, documenting developments and results achieved. Contribute to projects that require grasping activities in robots. Prepare and submit a scientific paper to a relevant conference or journal in the robotics or AI area.

Academic Qualifications

Bachelor’s Degree in

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Job ID: 256553

INESC TEC | Research Grant (AE2025-0187)
INESC TEC

Research Opportunities

Engineering

Work description

Study and implement a distributed architecture to support the execution of MLLMs. Propose solutions to evaluate trade-offs between computation, communication, and latency. Study the state of the art in MLLMs applicable to the task of analyzing industrial machine operations. Develop and optimize the computer vision pipeline. Create a performance evaluation system for the models. Document the developed solutions.

Academic Qualifications

Degree in Informatics, Electrical and Computer Engineering, Computer Science or similar.

Minimum profile required

Programming experience (Python, Go, others).

Preference factors

Experience in machine learning models, image processing, computer vision or machine learning, and particularly MLLMs, OR Experience in distributed systems and distributed workload management systems. Previous research experience.

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RSS Feed Source: Academic Keys

Job ID: 256552

INESC TEC | Research Initiation Grant (AE2025-0187)
INESC TEC

Research Opportunities

Telecommunications

Work description

Survey the state of the art in emerging wireless networks, including their simulation using real data assimilation, machine learning, and digital twin approaches; Collaborate in the writing of technical reports on communications protocols, algorithms, and mechanisms developed; – develop new modules enabling the simulation and/or experimentation of emerging wireless networks; Develop algorithms for the aggregation and management of multimodal wireless networks tailored for operation in maritime scenarios; Write publications in co-authorship within the scope of the work developed; Write the final activity report of the grant.

Academic Qualifications

Student in Electrical Engineering or similar.

Minimum profile required

Solid knowledge in TCP/IP stack and Linux; Programming skills in C++ and Python;

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