Research Assistant, Data Privacy in Machine Learning

School of Computing; Singapore; On-site; SGD 20,000 - 60,000; Full time

Job summary

An innovative institution is seeking a Research Assistant to contribute to groundbreaking work in privacy-preserving machine learning. This role involves designing algorithms and conducting experiments to ensure data security in sensitive applications across various sectors, including healthcare and finance. The successful candidate will collaborate closely with industry partners to translate research into practical solutions. Join a dynamic team committed to advancing the field of computer science and making a significant impact on society through cutting-edge research and development.

Qualifications

• Experience with privacy-preserving machine learning frameworks.
• Strong background in algorithms and data analysis.

Responsibilities

• Design and implement algorithms for privacy-preserving ML frameworks.
• Conduct experiments and analyze datasets for robust privacy guarantees.

Skills

Differential Privacy

Federated Learning

Secure Multi-Party Computation

Algorithm Design

Data Analysis

Education

Bachelor's Degree in Computer Science

Master's Degree in Computer Science

Job description

The National University of Singapore invites applications for the position of Research Assistant in the Department of Computer Science, School of Computing (SoC). SoC is strongly committed to research excellence in all its dimensions: Searching for fundamental results and insights, developing novel computational solutions to a wide range of applications, building large-scale experimental systems and improving the well-being of society. We seek to play an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems.

The Research Assistant will be working on developing privacy-preserving ML frameworks, with a focus on techniques such as differential privacy, federated learning, and secure multi-party computation. Responsibilities include designing and implementing algorithms, conducting experiments, and analyzing datasets to ensure robust privacy guarantees in ML models. The role demands hands-on collaboration with industry partners to translate research outcomes into practical solutions for sectors like healthcare, finance, or technology, where data sensitivity is paramount.