QEC Research Intern (PhD): Quantum Systems & Algorithms

Riverlane; Boston (MA); Hybrid; USD 110,000 - 125,000; Full time

Job summary

Riverlane invites applications for a PhD Internship in Boston focusing on research in quantum error correction (QEC). You will work with Riverlane’s researchers to simulate, run and decode QEC experiments, framing a project at the intersection of quantum theory, simulations and hardware-software co-design.

Based in the US with a supervisor, you will study noise models, efficient simulations and QEC decoding methods while contributing to scalable quantum computing efforts at Riverlane.

Qualifications

• Pursuing a PhD in a relevant technical field (Physics, Mathematics, Computer Science, Computer Engineering, Electrical Engineering).
• Experience with quantum information or error correction is a plus.
• Authorization to work in the United States for the duration of the internship.

Responsibilities

• Develop algorithms, simulations or architectural models to evaluate potential QEC approaches.
• Investigate methods to reduce compute, communication, memory, latency or power for QEC.
• Explore trade-offs between decoding performance and classical resource requirements.
• Collaborate with quantum scientists and engineers across theory, decoding, software and hardware.
• Analyze results and communicate findings through discussions, presentations and reports.
• Produce clear, reproducible research code and documentation.

Skills

Python

C

C++

Analytical thinking

Communication

Problem solving

Collaborative

Education

PhD candidate in Physics/Math/CS/CE/EE

Tools

Python

C

C++

Job description

Riverlane invites applications for a PhD Internship in Boston focusing on research in quantum error correction (QEC). You will work with Riverlane’s researchers to simulate, run and decode QEC experiments, framing a project at the intersection of quantum theory, simulations and hardware-software co-design.

Based in the US with a supervisor, you will study noise models, efficient simulations and QEC decoding methods while contributing to scalable quantum computing efforts at Riverlane.