Quantum Scientist – New York City Suburbs
Position Description:
We are seeking an experienced Quantum Scientist to conduct research and development on applying novel quantum or physics-inspired computing hardware to computationally hard optimization problems. This role involves close collaboration with both application-focused teams and hardware engineering teams to translate theoretical models into practical implementations.
Key Responsibilities:
- Design, analyze, and implement algorithms for combinatorial optimization and related computationally challenging problems on advanced computing hardware.
- Collaborate with hardware engineers to map theoretical models and algorithms to physical implementations.
- Benchmark quantum or physics-inspired computing approaches against classical and alternative quantum methods, and publish results in peer-reviewed venues.
- Develop simulation and modeling tools to characterize system performance and scalability.
- Contribute to interdisciplinary projects at the intersection of physics, computer science, and applied mathematics.
- Partner with application teams to identify high-impact use cases across industry and government sectors.
- Communicate technical results and insights to both technical and non-technical audiences, including collaborators, customers, and leadership.
Required Skills and Experience:
- PhD in Quantum Information Science, Physics, Computer Science, Applied Mathematics, or a related field.
- Strong foundation in quantum algorithms, quantum information theory, or statistical/quantum physics.
- Demonstrated research experience in optimization methods, either quantum or classical.
- Proficiency in scientific programming (e.g., Python, C++, or similar) and numerical methods.
- Strong publication record or equivalent technical contributions.
- Ability to work collaboratively across disciplines and clearly communicate complex ideas.
Preferred Qualifications:
- Experience with NISQ-era hardware, analog quantum devices, or non-traditional computing paradigms.
- Familiarity with physics-based or entropy-inspired computing models for optimization.
- Background in high-performance computing, large-scale simulations, or hybrid classical–quantum workflows.
- Experience with combinatorial optimization formulations such as Ising models, QUBO, or constraint satisfaction problems.
- Industry or government R&D experience applying advanced computational techniques to real-world problems.
- Demonstrated leadership and mentoring experience in research environments.
Featured benefits
Medical insurance, Vision insurance, Dental insurance, 401(k), Pension plan, Child care support, Paid maternity leave, Paid paternity leave, Commuter benefits