Salary
≈ $160k – $327k per year (Estimated)
Location
Hybrid (Los Angeles, United States)
Seniority
Staff
Employment
Full-Time
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 15, 2026.
Overview
Company
Impact
Profile match
Infrastructure software to power the quantum future. We expand the utility of quantum computers and deliver new quantum sensing capabilities through software.
Backed by DCVC, Sierra Ventures, Alpha Edison
About the role
- Q-CTRL’s Applications & Algorithms team develops quantum algorithms and application workflows aimed at making quantum computers useful. We are seeking a Staff Research Scientist to help establish and lead our research program in fault-tolerant quantum applications.
- As quantum computing progresses toward error-corrected operation, an increasingly important question is not simply what can be demonstrated on today’s hardware, but which applications can justify future fault-tolerant quantum computers, what resources those applications will require, and how algorithmic innovation can bring those requirements within reach.
- In this role, you will identify compelling applications for fault-tolerant quantum computing and develop the algorithms, implementations, and quantitative resource analyses needed to understand when and how those applications can become useful. You will work from the application level down through algorithmic primitives and logical resource requirements, collaborating closely with researchers working in quantum error correction, compilation, control, and quantum software.
- This is an application-facing quantum-algorithms role rather than a quantum-error-correction role. Most of the work will involve theory, simulation, resource estimation, and research software, with selective use of contemporary quantum hardware or emerging logical-qubit systems where experiments can validate important algorithmic primitives or assumptions.
- Scientific simulation, quantum chemistry, and many-body physics are important areas of interest, but we are also interested in new application classes where there is a compelling and quantitatively defensible case for quantum advantage.
What you'll be doing:
- Identify, formulate, and prioritize applications that offer credible opportunities for useful fault-tolerant quantum computation.
- Design, implement, and analyze quantum algorithms for scientifically or commercially relevant problems.
- Translate high-level algorithms into explicit logical workloads and quantify requirements including logical qubits, non-Clifford resources, circuit depth, measurements, runtime, and space-time overhead.
- Develop algorithmic improvements that materially reduce the resource cost of fault-tolerant computation, including improvements to problem formulation, state preparation, Hamiltonian representation, measurement, and algorithmic primitives.
- Establish rigorous classical baselines and quantitative criteria for assessing potential quantum advantage.
- Build and maintain high-quality research software for algorithm implementation, simulation, benchmarking, and resource estimation.
- Work closely with Q-CTRL researchers in quantum error correction, circuit synthesis, compilation, and control to understand how application algorithms interact with realistic fault-tolerant architectures.
- Use contemporary quantum hardware or early logical-qubit systems selectively where small-scale experiments can validate relevant algorithms, primitives, or assumptions.
- Initiate and lead ambitious research projects, mentor other researchers, and help shape the technical direction of Q-CTRL’s Applications & Algorithms team.
- Collaborate with engineering and product teams to translate research results into reusable capabilities and insights relevant to Q-CTRL’s technology roadmap.
- Publish and present your research in peer-reviewed journals and at leading conferences, and engage with external academic, government, and industrial collaborators.
- Communicate technical work clearly to both expert and broader technical audiences.
Ideally you'll have:
- An advanced degree in Physics, Computer Science, Mathematics, Chemistry, Engineering, or a related discipline. A PhD is strongly preferred, although exceptional candidates with equivalent research or industry experience will also be considered.
- Deep expertise in quantum computing and quantum algorithms, with a record of independently leading substantial research projects.
- Experience moving beyond asymptotic algorithmic results toward explicit implementations, numerical studies, or concrete resource estimates.
- A strong record of impactful research, demonstrated through publications, software, patents, presentations, or equivalent technical contributions.
- Strong scientific-programming skills, particularly in Python, and experience developing reliable research software.
- The ability to reason critically about both quantum and classical algorithms and to construct credible classical baselines.
- Broad scientific judgment and the ability to identify important research problems, set technical direction, and carry projects from initial concept through quantitative validation.
- Experience using large language models or AI agents to accelerate scientific research, including tasks such as literature synthesis, hypothesis generation, code development, automated experimentation, or scientific reasoning.
- Strong communication and collaboration skills, including the ability to work effectively across quantum algorithms, error correction, compilation, software engineering, and application domains.
Skills we also value (one or more is desirable, but not required):
- Hamiltonian simulation, quantum phase estimation, quantum signal processing or QSVT, block encoding, amplitude estimation, or other techniques relevant to large-scale quantum algorithms.
- Quantum chemistry, many-body physics, materials simulation, or other scientific-computing applications.
- Fault-tolerant resource estimation or logical circuit synthesis.
- Working knowledge of quantum error correction and fault-tolerant architectures.
- HPC, GPU computing, tensor-network methods, or other advanced classical simulation techniques.
- Experience executing algorithms on contemporary quantum hardware.
- Quantum compiler development or circuit optimization.
- Rigorous quantum-learning theory or other emerging application areas with a credible route to quantum computational advantage.
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