Position Overview

Research Responsibilities

1. Assist in conducting cutting-edge research on AI security theories and technologies, with a focus on large language models (LLMs), agents, and distributed learning paradigms. Key research areas include LLM security, Agent security, and federated learning security.
2. Support research on graph and temporal graph representation learning, with an emphasis on graph anomaly detection under dynamic topologies. The goal is to improve the accuracy and robustness of detection methods in complex real-world scenarios.
3. Aid in exploring multi-agent security issues, aiming to enhance the security and robustness of multi-agent collaboration through the study of cooperative decision-making mechanisms, adversarial defense strategies, and system fault tolerance.
4. Collaborate with the research team to draft academic papers, participate in laboratory discussions, and assist in relevant academic exchanges and research collaborations.

Qualifications & Requirements

1. For Prospective Masters Students: Currently pursuing or about to pursue a bachelor’s degree in Computer Science, Electrical Engineering, Statistics, Data Science, Mathematics, or a closely related field, with a strong desire to pursue a master’s degree in AI security or cybersecurity.
2. For Interns: Currently pursuing a bachelor’s or master’s degree in the above-mentioned fields, with the ability to commit to on-site work for at least 5 consecutive months.
3. Possess basic to solid proficiency in core AI theories and technologies, including deep learning, Transformer architecture, reinforcement learning, or Agentic AI. Practical experience with programming languages (e.g., Python, TensorFlow/PyTorch) is required.
4. Have a keen interest in AI security, with a strong theoretical foundation or potential in related fields. Previous research experience or project experience in AI, machine learning, or cybersecurity is a plus.
5. Have a proactive attitude towards research, a passion for exploring new technologies, and the ability to learn quickly and tackle research tasks efficiently.

Application Instructions

• Curriculum Vitae (CV) including educational background, academic achievements, research/project experience (if any), and other relevant information.
• A brief personal statement (500 words or less) outlining your academic interests, career goals, and reasons for applying (especially relevant to AI security research).
• For prospective masters students: Academic transcripts (undergraduate, if applicable) and a letter of recommendation (optional but preferred).