Quantum Characterization Scientist

Overview

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This range is provided by Johns Hopkins Applied Physics Laboratory. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

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Are you a theorist with expertise in noise characterization or performance evaluation of quantum systems? Are you looking to take part in impactful research in quantum information science? Do you want to work with a vibrant team of experimental and theoretical physicists?

We’re looking for a creative quantum scientist to help us grow new projects and mature existing ones in quantum characterization, verification, and validation (QCVV). As a member of our team, you’ll contribute to the development and evaluation of noise and performance characterization approaches and characterization-informed error protection strategies for quantum systems. This includes working with experimental researchers to empirically validate said protocols.

You will join our hardworking team of quantum scientists who are passionate about building new and exciting solutions to expand the state-of-the-art in quantum science. We strive to foster an environment of collaboration and teamwork. Our team is committed to integrity and honesty, and values substance and innovation.

As a Quantum Characterization Scientist at APL you will...

• Investigate the fundamental limits of existing QCVV approaches with respect to sampling/computational complexity, estimation-theoretic properties, and assumptions on the error and/or underlying physical systems.
• Identify avenues for improvement and extensions beyond current limits of existing QCVV protocols, and implement them.
• Use advanced statistical, signal processing, machine learning and/or optimization techniques to develop and implement accurate and efficient QCVV protocols that are scalable with respect to computational resources (i.e., qubit count and runtime).
• Interpret and map QCVV metrics to both low-level physical/device properties and high-level performance of quantum algorithms (including quantum error correction).
• Trace high-level performance to physical properties and measure/validate improvements at the qubit/device level to make predictions about improved high-level performance.
• Work closely with our experimental team to execute existing and novel QCVV protocols.

You will meet our minimum qualifications if you…

• Have a PhD in Physics, Mathematics, Computer Science, Electrical Engineering, Statistics or closely related field.
• Have 1+ years of post-doctoral (or equivalent) experience in quantum information science.
• Have experience with common qubit benchmarking and tomographic protocols (e.g., randomized benchmarking and its variations, as well as Hamiltonian, state, process, and gate-set tomography).
• Have experience with programming and software development.
• Have a proved record of research accomplishments and publications in the field of quantum information science.
• Are willing to occasionally travel to sponsor sites, conferences, workshops.
• Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain TS/SCI+poly level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You will go above and beyond our minimum requirements if you…

• Have experience with high-performance computing.
• Have experience with methods for classical simulation of quantum systems, e.g., using tensor networks.
• Have experience in machine learning and its application to QCVV.
• Have experience with common signal processing and estimation theory techniques, e.g., compressed sensing and Bayesian estimation.
• Have experience with quantum error correction.
• Have experience working closely with experimentalists.
• Have a proven record of impactful research accomplishments.
• Have an active TS/SCI w/ Polygraph security clearance.

The Johns Hopkins University Applied Physics Laboratory (APL)…