Research Fellow (Artificial Intelligence Machine Learning Robotics)

Nanyang Technological University

Job Location:

Singapore - Singapore

Monthly Salary: Not Disclosed

Posted on: 3 hours ago

Vacancies: 1 Vacancy

Job Summary

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 3000 undergraduates students and 2000 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 worlds largest engineering schools that nurtures 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: are looking for a Research Fellow to focus on open-source processor and accelerator architectures. The role focuses on advancing research in integrated circuit (IC) design and electronic design automation (EDA) with particular emphasis on RISC-V based processors AI accelerators and open-source hardware toolchains. The Research Fellow contributes to the Universitys mission by conducting high-impact research developing innovative hardware architectures and design methodologies and disseminating research outcomes through publications collaborations and open-source contributions.

Key Responsibilities:

Develop accelerated AI/ML and robotics algorithms that significantly reduce computation cost memory footprint and power consumption.
Design and optimize efficient training and inference pipelines for foundation models (LLM VLM VLA) across different model sizes and deployment settings.
Apply and advance model compression techniques including quantization pruning knowledge distillation low-rank adaptation and related methods.
Conduct algorithm-hardware co-design to enable efficient and accurate deployment of AI algorithms on robotic edge and heterogeneous computing platforms.
Develop methods for efficient deployment of AI models on cloud and edge devices considering latency throughput and energy constraints.
Implement evaluate and benchmark accelerated models using rigorous experimental protocols.
Contribute to research publications in top-tier AI ML and robotics conferences and journals.
Supervise and mentor PhD students junior Research Assistants and Master students.
Collaborate with interdisciplinary teams spanning AI systems and robotics.
Contribute to open-source codebases and reproducible research practices.

Job Requirements:

A completed PhD in Computer Science Electrical Engineering Robotics Artificial Intelligence or a closely related discipline.
Strong research background in AI and machine learning with a focus on efficient or accelerated models.
Proven experience with model compression techniques such as quantization pruning distillation and low-rank adaptation.
Demonstrated experience working with foundation models particularly vision-language models (VLMs); experience with LLMs or VLAs is a strong advantage.
Solid understanding of algorithm-hardware co-design especially for robotics or edge AI deployment.
Strong programming skills in C C and Python with experience in deep learning frameworks such as PyTorch or TensorFlow.
Familiarity with deployment constraints on cloud edge or embedded systems.
Experience in robotics embodied AI or autonomous systems is an advantage.
Strong publication record or clear potential to publish in leading international venues.
Demonstrated ability to lead research projects supervise researchers and mentor junior staff.
Ability to work independently manage complex research tasks and collaborate effectively in interdisciplinary teams.
Good written and oral communication skills.

We regret to inform that only shortlisted candidates will be notified.

Hiring Institution: NTU

Key Responsibilities:

Develop accelerated AI/ML and robotics algorithms that significantly reduce computation cost memory footprint and power consumption.
Design and optimize efficient training and inference pipelines for foundation models (LLM VLM VLA) across different model sizes and deployment settings.
Apply and advance model compression techniques including quantization pruning knowledge distillation low-rank adaptation and related methods.
Conduct algorithm-hardware co-design to enable efficient and accurate deployment of AI algorithms on robotic edge and heterogeneous computing platforms.
Develop methods for efficient deployment of AI models on cloud and edge devices considering latency throughput and energy constraints.
Implement evaluate and benchmark accelerated models using rigorous experimental protocols.
Contribute to research publications in top-tier AI ML and robotics conferences and journals.
Supervise and mentor PhD students junior Research Assistants and Master students.
Collaborate with interdisciplinary teams spanning AI systems and robotics.
Contribute to open-source codebases and reproducible research practices.

Job Requirements:

A completed PhD in Computer Science Electrical Engineering Robotics Artificial Intelligence or a closely related discipline.
Strong research background in AI and machine learning with a focus on efficient or accelerated models.
Proven experience with model compression techniques such as quantization pruning distillation and low-rank adaptation.
Demonstrated experience working with foundation models particularly vision-language models (VLMs); experience with LLMs or VLAs is a strong advantage.
Solid understanding of algorithm-hardware co-design especially for robotics or edge AI deployment.
Strong programming skills in C C and Python with experience in deep learning frameworks such as PyTorch or TensorFlow.
Familiarity with deployment constraints on cloud edge or embedded systems.
Experience in robotics embodied AI or autonomous systems is an advantage.
Strong publication record or clear potential to publish in leading international venues.
Demonstrated ability to lead research projects supervise researchers and mentor junior staff.
Ability to work independently manage complex research tasks and collaborate effectively in interdisciplinary teams.
Good written and oral communication skills.

We regret to inform that only shortlisted candidates will be notified.

Hiring Institution: NTU

Key Skills

Bioinformatics
Genetics
R
Biochemistry
Cell Biology
Research Experience
Statistical Software
Cell Culture
Molecular Biology
Data Analysis Skills
Flow Cytometry
Microscopy

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About Company

Nanyang Technological University

Nanyang Technological University is one of the top universities in Singapore offering undergraduate and postgraduate education in engineering, business, science, humanities, arts, social sciences, education and medicine.

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