SuperQubit is building the algorithmic foundation for a new class of physics-informed quantum software, with applications across optimization, materials and molecular simulation, and quantum-enhanced machine learning. We are seeking a Quantum Algorithm Research Scientist to take long-term ownership of our algorithm development pipeline — from theoretical concept through hardware deployment.
This is a senior technical role intended for someone who has completed both a PhD and (ideally) a postdoctoral appointment, or who has equivalent industrial research experience.
Role Overview
The Research Scientist will own the design, implementation, and validation of SuperQubit’s proprietary algorithm portfolio. They will translate physically motivated models of interacting many-body systems into hardware-executable quantum circuits, lead benchmarking and execution campaigns on quantum hardware, and contribute substantively to the company’s technical direction and intellectual property strategy. The role combines deep research with the pragmatism required to ship working software on real devices.
Key Responsibilities
- Architect and develop SuperQubit’s algorithm portfolio, including novel approaches for optimization, simulation, and quantum machine learning.
- Translate theoretical models of correlated, long-range interacting systems into efficient quantum circuit representations with rigorous resource analysis.
- Lead end-to-end execution on quantum hardware: compilation, noise-aware optimization, error mitigation, and benchmarking against classical and quantum baselines.
- Contribute to patent disclosures and intellectual property strategy.
- Establish internal scientific standards, code review practices, and technical documentation.
- Mentor postdocs and PhD interns; participate in technical hiring.
- Represent SuperQubit in selected scientific venues, conferences, and partnership discussions with hardware providers and academic collaborators.
Minimum Requirements
- PhD in Physics, Quantum Information, Applied Mathematics, Computer Science, or a related discipline, with at least 2 years of additional research experience (postdoctoral, industry research, or equivalent).
- Substantial publication record in quantum algorithms, quantum simulation, or related areas, including first-author work.
- Demonstrated expertise in many-body quantum physics, fermionic and bosonic systems, and the mathematics of interacting quantum systems.
- Deep practical knowledge of Hamiltonian simulation, fermionic encodings, and circuit compilation for noisy and near-term hardware.
- Documented track record of running quantum algorithms on multiple real hardware platforms (e.g., superconducting, trapped-ion, neutral-atom).
- Advanced Python proficiency and fluency with at least two quantum programming frameworks (Qiskit, PennyLane, Cirq, Braket).
- Strong understanding of error mitigation, error correction primitives, and the trade-offs of NISQ-era execution.
- Must reside in or be willing to relocate to the Greater Toronto Area.
Preferred Qualifications
Existing relationships with hardware providers (IBM Quantum, IonQ, Quantinuum, Rigetti, PsiQuantum, etc.).
Background in correlated electron systems, condensed matter theory, or post–Hartree-Fock quantum chemistry.
Experience with classical many-body simulation tools (tensor networks, DMRG, quantum Monte Carlo) as a baseline for quantum advantage analysis.
Prior experience leading research teams or projects in an industrial or national-lab setting.
Patent or invention disclosure history.
Experience designing physics-informed quantum machine learning methods, including kernel methods, quantum feature maps, or generative models grounded in physical priors.
Familiarity with HPC environments and large-scale classical simulation infrastructure.
Job Type: Full-time
Pay: $60,000.00-$130,000.00 per year
Application question(s):
- Are you located in the Greater Toronto Area?
- Are you a Canadian permanent resident or citizen?
Work Location: Hybrid remote in Markham, ON L3R 5Y6
