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SuperQubit Inc.Source d’offres vérifiée

Quantum Algorithm Research Scientist

Offre en anglais

The role involves designing and implementing a proprietary portfolio of quantum algorithms for optimization, simulation, and machine learning. The scientist will translate theoretical models into hardware-executable circuits and lead benchmarking campaigns on real quantum hardware.

  • Hybride
  • Markham, ON
  • Publié 5 août 2026
  • Postuler avant le 4 sept. 2026
  • 1 poste

Résumé du poste

Job Position: Quantum Algorithm Research Scientist Office Location: 7303 Warden Ave, Markham, ON L3R 5Y6 (Hybrid) Employment Type: Full‑time, Permanent Experience Level: Senior Technical Application Email: [email protected] 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. How to Apply Interested candidates should submit a CV, a research and vision statement (max three pages), and the names of three references.

Ce que vous ferez

The role involves designing and implementing a proprietary portfolio of quantum algorithms for optimization, simulation, and machine learning. The scientist will translate theoretical models into hardware-executable circuits and lead benchmarking campaigns on real quantum hardware.

Exigences

Candidates must hold a PhD in a relevant field with at least 2 years of additional research experience and a strong publication record. Proficiency in Python and multiple quantum programming frameworks, along with a track record of running algorithms on real hardware, is required.

Compétences indiquées

  • PythonSouhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

  • Quantum Algorithm Design
  • Quantum Simulation
  • Quantum Machine Learning
  • Hamiltonian Simulation
  • Circuit Compilation
  • Error Mitigation
  • Python
  • Qiskit
  • PennyLane
  • Cirq
  • Braket
  • Many-Body Quantum Physics
  • Fermionic Encodings
  • Resource Analysis
  • Intellectual Property Strategy
  • Benchmarking

Domaines d’emploi

  • Science & Research
  • Technology
  • Software
  • Engineering
  • Data & Analytics

Renseignements supplémentaires

Formation minimale
Maîtrise
Expérience minimale
5+ ans
Postuler avant le
4 sept. 2026
Langue de l’offre
anglais
Heures de travail
40 heures par semaine
Niveau d’expérience
Mid-Senior level