AI Research Specialist

3 days ago


Singapore NTU (Nanyang Technology University- Main Office-HR) Full time

Nanyang Technological University's (NTU) National Centre for Research in Digital Trust (DTC) is a trust technology research centre dedicated to executing a national programme that puts Singapore at the forefront of trust hubs. The key objective is to support efforts in creating a trusted digital environment for people and businesses undergoing digital transformation, providing assurance and confidence as they digitalise.

We are seeking an experienced Research Fellow to join our Digital Trust Centre, focusing on multi-modal model testing. As a member of our interdisciplinary team, you will contribute to cutting-edge research in Generative AI, designing, developing, and optimising multi-modal Large Language Models (LLMs).

Key Responsibilities:

  • Conduct advanced research in Generative AI, investigating and implementing methodologies to ensure AI authenticity, accountability, and the integrity of digital content.
  • Develop and refine machine learning and deep learning algorithms, including machine unlearning techniques, to enhance model robustness and reliability.
  • Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems.
  • Collaborate with interdisciplinary teams to align AI research with ethical standards and best practices in AI safety.
  • Publish findings in top-tier conferences and journals, contributing to the broader AI and machine learning research community.

Job Requirements:

  • PhD degree in computer science/engineering or related field.
  • Proficiency in Python is essential; experience with other programming languages such as Java, C/C++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous.
  • Background in Generative AI research, including multi-modal LLMs, and 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.
  • Understanding of ethical considerations and best practices in AI research, particularly concerning data privacy and security.
  • Competent in collaborative skills, with experience working in cross-functional teams.

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