Data Trust Internship - PhD (Summer 2023)

Seagate Research Group is seeking a motivated graduate student intern to join our edge analytics and data trust research team to explore the limitations of existing distributed, multi-party, machine learning algorithms. We are developing new approaches to overcome these limits.

 

We are seeking a research intern to contribute to the privacy preserving and secure system development inside Seagate. The ideal candidate will use techniques such as multi-party computing, differential privacy and/or secret sharing to design privacy-preserving algorithms for distributed machine learning at the edge, identify the potential attack models on federated learning and design algorithms to defend them, implement the designed algorithms on machine learning simulation software and tools, and publish the obtained results in peer-reviewed conference/journal venues. An alternative research topic is privacy preservation in DNA sequencing and compute. The goal is to design efficient algorithms to keep genome data private during DNA processing.

 

•   Currently enrolled in a PhD program 

•   Pursuing a degree in Computer science, Electrical engineering, Applied Math, or other related areas

•   Programming experience in Python, TensorFlow, PyTorch

•   Deep understanding of information-theoretic security concepts, e.g., threshold secret sharing scheme and multi-party computing

•   Experience with at least one of the following privacy technologies: Secure multi-party computation technologies, Differential privacy, Federated Learning, Learning on encrypted data, Homomorphic encryption, Trusted execution environments

•   Self-motivated, independent and a team player with strong communication and interpersonal skills

•   Attention to detail and proactive