Data Security and Privacy Student- Research Lab

Introduction
At IBM work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so lets talk.

Your Role and Responsibilities

Join the Data Security and Privacy group in IBM Research to contribute to cutting-edge technologies at the intersection between security/privacy and machine learning.
Our activities include both privacy in AI and AI for security & privacy. Current research directions include:

• LLM privacy model risk assessment and mitigation – technologies for attacking models such as to assess potential data leakage and mitigation measure e.g. differential privacy to create privacy-preserving models
• Quantum Safe discovery and remediation – technologies for discovery of cryptographic code that is unsafe or not ready for the qunatum era and using LLMs for code remediation
• Data Classification – technologies for detection of personal/confidential data within structured and unstructured repositories for scenarios such as compliance and AI/LLM lifecycle.

Join us to contribute to one of these fascinating and innovative areas with the goal of publishing results in top conferences/journals and contributing to leading open-source projects. This is an opportunity to work on advanced research topics but bringing them into the context of real-world scenarios and use cases based on real customer pain-points.

Required Technical and Professional Expertise

Preferred Technical and Professional Expertise
Knowledge in privacy related technology data protection attacks/defences on ML models ML explainability maths/statistics theory.