PhD Position in Cryptographic Proof Systems

IBM Research Zurich seeks a PhD candidate to design efficient cryptographic proof systems for secure cloud and privacy applications. This full-time hybrid role offers four years of funding and potential EPFL supervision.

The successful candidate will join a research initiative dedicated to advancing cryptographic proof systems. The primary objective is to create methods that significantly lower time and memory costs, thereby enabling efficient verification of large-scale computations. This work supports broader goals in secure cloud computing, verifiable machine learning, and privacy-preserving technologies.

Responsibilities

• Design and implement novel proof systems that minimize computational time and memory usage.
• Apply mathematical disciplines such as algebra, combinatorics, and probability to analyze and improve algorithmic efficiency.

Requirements

• Hold an MSc degree or equivalent qualification in Computer Science, Mathematics, or a closely related discipline.

Nice to have

• Demonstrated expertise in cryptographic proof systems, including zero-knowledge proofs and succinct arguments.
• Solid understanding of error-correcting codes and coding theory.
• Experience with streaming algorithms and techniques for memory-efficient computation.
• Knowledge of lightweight cryptography methods.

What the company offers

• Four-year funding package for the research position.
• Opportunity for joint supervision with EPFL.
• Access to a multicultural research setting that encourages diverse perspectives and flexible work arrangements.
• Commitment to supporting a healthy balance between professional duties and personal life.

About the company

IBM Research Zurich operates within a culture that prioritizes diversity and inclusion. The organization is dedicated to creating an environment where individuals of all genders and backgrounds can succeed and thrive in their professional careers.

• Fostering a diverse and inclusive workplace culture.
• Supporting professional growth for employees from all backgrounds and genders.
• Valuing different perspectives within the research team.