Research Fellow (Computer Science / Engineering) (R00019925)

Nanyang Technological University; Singapore; On-site; USD 60,000 - 100,000; Full time

Job summary

An established industry player is seeking a talented researcher to join their National Centre for Research in Digital Trust. This exciting role focuses on advancing Generative AI and multi-modal large language models, ensuring AI authenticity and accountability. You will collaborate with interdisciplinary teams, develop innovative algorithms, and contribute to the AI research community through publications. If you are passionate about AI safety and eager to make a significant impact in a fast-paced environment, this opportunity is perfect for you.

Qualifications

• PhD degree in computer science or related fields required.
• Proficiency in Python and experience with machine learning models essential.

Responsibilities

• Conduct advanced research in Generative AI and multi-modal LLMs.
• Develop and refine machine learning algorithms to enhance model reliability.

Skills

Python

Machine Learning

Deep Learning

Natural Language Processing

Generative AI

Analytical Skills

Problem-Solving

Communication Skills

Education

PhD in Computer Science/Engineering

Tools

PyTorch

TensorFlow

Java

C/C++

Go

Job description

Nanyang Technological University’s National Centre for Research in Digital Trust (DTC) is a Trust Technology Research Centre to execute a national program to help put Singapore into a strong trust hub. The key objective is to support efforts to create a trusted digital environment for people and businesses in the digital transformation by providing businesses and consumers with greater assurance and confidence as they digitalize.

For more details, please view https://www.ntu.edu.sg/dtc

Key Responsibilities:

• Conduct advanced research in Generative AI, focusing on the design, development, and optimization of multi-modal LLMs.

• Investigate and implement 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 Requirement:

• PhD degree 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 reserach, including multi-modal LLMs.

• Background in AI Safety research, inlcuding 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.

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