PhD Position F/M PhD Position F/M: How does Reasoning with LLM Help Repair Vulnerabilities in Repo-level Software Projects?

Eligibility requirements

• To successfully carry out the research objectives of WP2 and WP3, the ideal candidate should possess a strong foundational background in both artificial intelligence and software security. We are looking for candidates who meet the following requirements:
• Educational Background: A Master’s degree or equivalent engineering degree in Computer Science, Artificial Intelligence, Cybersecurity, or a closely related discipline.
• Deep Learning Expertise: Solid knowledge and proven project experience in designing, training, and evaluating Deep Neural Network (DNN)-based classification models.
• Program Analysis Proficiency: Demonstrated understanding and practical experience in program analysis. Specifically, the candidate must be familiar with the static analysis of source code using semantic representations, such as Control Flow Graphs (CFG) and Data Flow Graphs (DFG).
• Programming Skills: Strong programming skills in Python and proficiency with standard deep learning frameworks (e.g., PyTorch, TensorFlow). Experience with code parsing and analysis tools (e.g., Tree-sitter, Joern) is highly desirable.
• Additional Assets: Prior exposure to Large Language Models (LLMs), Natural Language Processing (NLP), or Adversarial Machine Learning will be considered a significant plus.
• Soft Skills: Excellent analytical and problem-solving skills, an autonomous and rigorous work ethic, and good communication skills in English for scientific writing and presentation within an international consortium.