Deskripsi Pekerjaan
Join the cutting-edge research frontier at NTU's prestigious ROSE Lab, where you'll pioneer solutions to one of the most pressing challenges in digital security. As a Research Associate specializing in deepfake detection, you'll develop innovative forensic techniques to identify and combat manipulated media. This role offers unparalleled opportunities to publish high-impact research, collaborate with world-class researchers, and contribute to Singapore's position as a global innovation hub. You'll work with state-of-the-art computational resources while exploring advanced machine learning and computer vision methodologies to detect digital tampering across images and videos.
NTU provides a dynamic, interdisciplinary research environment with access to cutting-edge facilities and industry partnerships. The position includes competitive compensation, comprehensive benefits, and professional development opportunities. Ideal candidates passionate about ethical technology and digital integrity will find this role intellectually stimulating and professionally rewarding.
Tanggung Jawab
- Lead cutting-edge research projects in deepfake detection and digital forensics
- Design and implement novel algorithms for identifying manipulated media artifacts
- Conduct rigorous experiments and performance evaluations of detection methodologies
- Collaborate with multidisciplinary teams to develop integrated security solutions
- Prepare high-impact research publications for top-tier conferences and journals
- Stay current with emerging threats in media manipulation and countermeasures
- Contribute to grant proposals and research funding initiatives
Kualifikasi
- Master's or PhD degree in Computer Science, Electrical Engineering, or related field
- Strong expertise in computer vision, machine learning, and deep neural networks
- Proven experience with deepfake detection, image processing, or digital forensics
- Proficiency in Python, TensorFlow, PyTorch, and related ML frameworks
- Excellent analytical skills and ability to design robust experimental methodologies
- Strong publication record in peer-reviewed conferences or journals
- Ability to work independently and collaboratively in cross-functional teams