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1 week ago
About Us
Nanyang Technological University's (NTU) National Centre for Research in Digital Trust (DTC) is a leading research centre focused on executing a national program to establish Singapore as a strong trust hub. Our key objective is to support efforts to create a trusted digital environment for people and businesses in the digital transformation by providing assurance and confidence as they digitalize.
Key Responsibilities:
- We conduct advanced research in Generative AI, focusing on the design, development, and optimization of multi-modal Large Language Models (LLMs).
- We investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content.
- We develop and refine machine learning and deep learning algorithms, including machine unlearning techniques, to enhance model robustness and reliability.
- We design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems.
- We collaborate with interdisciplinary teams to align AI research with ethical standards and best practices in AI safety.
- We publish findings in top-tier conferences and journals, contributing to the broader AI and machine learning research community.
Requirements:
- PhD in computer science/engineering or related fields.
- Proficiency in Python is a must. Experience with other programming languages such as Java, C/C++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous.
- Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large language models (LLMs), including tasks such as data preprocessing, feature extraction, model training, and evaluation.
- Background in Generative AI research, including multi-modal LLMs.
- Background in AI Safety research, including AI authenticity, accountability, and integrity of digital content.
- Strong knowledge of machine learning and deep learning techniques, including machine unlearning, and AI testing.
- Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders, bridging the gap between research and practical application.
- Strong analytical and problem-solving skills, with a focus on developing innovative solutions for multi-modal LLMs.
- Self-motivated and able to work independently, managing multiple tasks and projects in a fast-paced environment.
- Strong collaborative skills, with experience working in cross-functional teams.
- Keen attention to detail and commitment to high-quality deliverables.
- Understanding of ethical considerations and best practices in AI research, particularly concerning data privacy and security.
