Research Scientist Intern, Privacy Technologies (PhD)

Core Data Science (CDS) is a research and development team, working to improve Meta’s products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on longer-term, foundational work that addresses new opportunities and challenges across the Meta products. The work we do enhances the Meta family of apps that enable billions of people to communicate with each other daily. Core Data Science is interdisciplinary, with expertise in computer science, statistics, machine learning, cryptography, among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at Meta and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise. We are looking for Research Scientist Interns to join the Statistics & Privacy team in CDS to advance cutting-edge applied research, focusing on Privacy Enhancing Technologies. Research Scientist Interns partner with our full-time Research Scientists to drive forward the research, prototypes and methodologies.Challenges and intern projects include incorporating approaches such as multi-party computation, homomorphic encryption, trusted execution environments, differential privacy, and federated learning to develop privacy-focused solutions while maintaining performance at massive scale, including cryptographic protocols, algorithms & tooling for machine learning or analytics.

Required Skills

Research Scientist Intern, Privacy Technologies (PhD) Responsibilities:

• Identify specific, high-impact research opportunities to develop new and improve existing privacy-preserving solutions, e.g. private record linkage, privacy-preserving ML and analytics.
• Design and prototype new algorithms, optimization methods, and system architectures using privacy technologies.
• Learn new tools, systems, and programming languages quickly as required by the particular project you are working on.
• Apply communication skills to engage diverse audiences on technical topics and nuanced insights.
• Develop patent applications, white papers, conference presentations, and publications that are broadly appealing and accessible beyond a core scientific audience.

Minumum Qualification

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD in computer science, statistics, machine learning, or a related technical field, with an emphasis in privacy technologies
• Experience with modern machine learning techniques or cryptography fundamentals
• Experience with at least one of the following privacy technologies, Secure Multi-Party Computation techniques, Homomorphic Encryption, Trusted Execution Environments, Differential Privacy, Federated Learning or Distributed Learning, Privacy Leakage and Attacks
• 2+ years in Python or C-family (e.g., C++, Rust, Go)
• Experience with communicating analysis and establishing confidence among audiences who do not share your disciplinary background or training
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
• Must be currently enrolled in a full-time degree program and returning to the program after the completion of the internship/co-op

Preferred Qualification

Preferred Qualifications:

• Intent to return to degree-program after the completion of the internship/co-op
• Proven track record of achieving significant results as demonstrated by grants, open-source projects, fellowships, patents, as well as first-authored publications at leading workshops or conferences like NeurIPS, ICML, AAAI, ACM CCS, TheWebConf, USENIX Security, IACR Crypto etc.) or disciplinary journals