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We are seeking a highly accomplished Quantum Applications Researcher at Fujitsu Research of America, Inc. (FRA) to help advance our research and product strategy across quantum optimization, quantum AI/ML, quantum simulation, and quantum algorithmic primitives. This role is ideal for a researcher with a strong publication record, deep technical expertise, and the ability to translate cutting-edge quantum methods into practical applications for enterprise and scientific use cases.

The successful candidate will contribute to Fujitsu’s hybrid quantum computing platform, generate high-impact intellectual property, publish in leading venues, represent the company at conferences and industry events, and build collaborations with academic, government, and commercial partners across the US and Europe. This person will also work closely with clients to identify valuable quantum use cases and develop credible technical roadmaps from research prototypes to deployable solutions.

Key responsibilities:

1. Research:

• Lead advanced research initiatives in one or more of the following areas: quantum compilation, quantum optimization, quantum simulation, quantum chemistry, quantum algorithm design, quantum algorithmic primitives, or hybrid quantum-classical methods.
• Develop novel algorithms and proof-of-concept techniques that demonstrate the value of quantum approaches for real-world problems.
• Identify promising near-term and long-term quantum applications, including NISQ-era approaches and fault-tolerant algorithmic opportunities.
• Design and evaluate hybrid quantum-classical algorithms using simulators, quantum hardware backends, and classical high-performance computing resources.
• Publish high-quality research papers in leading quantum computing, physics, computer science, optimization, AI/ML, and application-domain venues. Generate patentable ideas to contribute to Fujitsu's IP portfolio.
• Represent Fujitsu at conference and industry events. Deliver technical presentations for both experts and executive audiences.
• Mentor junior researchers and interns.

1. Platform and product contribution:

• Contribute to the development of Fujitsu's hybrid quantum computing platform, including algorithmic libraries, application modules, noise-aware compilation techniques, and user-facing research capabilities.
• Collaborate with Fujitsu's platform team to convert research prototypes into robust, scalable, and reusable platform components
• Develop reproducible code, documentation, test cases, and technical examples that support internal teams, customers, and partners.

1. Collaboration:

• Build and maintain research collaborations with universities, national labs, technology partners, and quantum ecosystem organizations across the US and Europe.
• Identify opportunities for joint research programs, sponsored research, grant proposals and partnerships.
• Liaise with our global Fujitsu team to engage enterprise and government clients on quantum use cases.

Essential requirements:

1. PhD in Physics, Computer Science, Applied Mathematics, Electrical Engineering, Chemistry, Materials Science, or a closely related quantum-relevant field.
2. Minimum of 4+ years of research experience after PhD in quantum computing, quantum algorithms, quantum information, quantum simulation, quantum optimization, quantum machine learning, or a closely related area.
3. Strong research track record demonstrated through peer-reviewed publications, conference presentations, patents, open-source contributions, or recognized technical leadership.
4. Deep understanding of quantum algorithms, hybrid quantum-classical methods, and the practical limitations of current quantum hardware.
5. Demonstrated expertise in at least one of the following areas:

• Quantum optimization, including QAOA, variational optimization, quantum annealing, Ising/QUBO formulations, or combinatorial optimization.
• Quantum AI/ ML, including quantum kernels, variational quantum classifiers, quantum neural networks, generative models, quantum-enhanced learning methods, or AI/ ML for quantum systems.
• Quantum simulation, including Hamiltonian simulation, VQE, quantum chemistry, condensed matter systems, or materials simulation.
• Quantum algorithmic primitives, including amplitude estimation, phase estimation, QSVT, block encoding, quantum walks, or fault-tolerant algorithm design.

1. Ability to develop original research ideas and translate them into prototypes, publications, patents, and product-relevant capabilities.
2. Strong written and verbal communication skills, with the ability to engage both technical and non-technical audiences.
3. Experience collaborating across disciplines and working with researchers, partners, and external stakeholders.

Preferred qualifications:

1. Strong coding background in Python and experience developing research-grade or production-quality scientific software.
2. Hands-on experience with quantum software frameworks such as Qiskit, PennyLane, Cirq, Tket, or related tools.
3. Experience with AI/ML frameworks such as PyTorch, TensorFlow, JAX, scikit-learn, or related libraries.
4. Knowledge of at least one application domain, such as finance, energy, manufacturing, pharmaceuticals, quantum chemistry, or materials science.
5. Familiarity with NISQ-era hardware constraints, error mitigation, noise modeling, quantum resource estimation, or fault-tolerant resource analysis.

At Fujitsu, we are committed to creating a diverse and inclusive workplace where everyone feels valued and respected. We believe that diversity and inclusion are essential to our success, and we are committed to creating an environment where all employees can thrive.

We are an equal opportunity employer and prohibit discrimination and harassment of any kind based on race, color, religion, sex, national origin, age, disability, marital status, sexual orientation, gender identity or expression, genetic information, veteran status, or any other characteristic protected by law.

We believe that everyone has something to contribute, and we are committed to creating a workplace where everyone can reach their full potential.

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