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 undergraduates students and 1,000 graduate students it is one of the largest EEE schools in the world and ranks 10th in the field of Electrical & Electronic Engineering in the 2024 QS World University Rankings by Subjects.
Today, the School has become one of the world’s 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: https://www.ntu.edu.sg/eee
The Rapid-Rich Object SEarch (ROSE) Lab focuses on research in: (i) visual search & retrieval, (ii) video analytics & deep learning, and (iii) multimedia forensics & biometrics. Resources at the ROSE Lab consist of NTU faculty, researchers, PhD students, and visiting researchers from other institutions from around the world, as well as large-scale GPU computing facilities for deep learning. Learn more about ROSE Lab at http://rose.ntu.edu
Key Responsibilities:
The Research Associate will be responsible for research on Multimedia (Audio & Video) Forensics, Generative AI, as well as Hallucination Detection and Mitigation. The roles of this position include:
- Working in research teams on Multimedia Forensics projects in Generative AI, Hallucination Detection, and DeepFake Detection.
- Creation of large-scale datasets for research and algorithm evaluation.
- Be part of a research team in the execution of funded research projects.
- Assist in drafting of proposals for research grants in the above areas.
Job Requirements:
- Masters in Computer Science, Data Science, Electrical/Electronic Engineering, or related field.
- Research experience in Computer Vision, Multimedia Forensics, Deep Learning, Trustworthy Machine Learning, and AI Security, as well as working with large-scale datasets.
- Experience with deep learning for image/video understanding, Generative AI, hallucination detection & mitigation, and adversarial/backdoor/poisoning attack/defense is essential.
- Proficiency in software such as PyTorch, OpenCV, and programming languages such as Python and C/C++, as well as Linux (eg. Ubuntu) is essential.
- Knowledge of GPU computing, CUDA programming, optimization (eg. with TensorRT), and industry experience in engineering software development would be an advantage.
- Good inter-personal skills, with the ability to work with people from varied backgrounds.
- Excellent verbal and written communication skills.
- Entry level candidates are welcome to apply
We regret to inform that only shortlisted candidates will be notified.