You will identify high-value, mission-relevant problems, formulate them for analysis, develop and optimize algorithms, and build rigorous, reproducible benchmarks that distinguish evidence from speculation. You will provide technical contributions to government proposal writing. You will translate validated research into prototypes, reusable software assets, technical roadmaps, and client recommendations while mentoring colleagues and raising standards for technical rigor, reproducibility, and communication.
This role requires candidates to possess or be willing to seek, obtain, and maintain a U.S. government security clearance, as required for the work.
Recruiting for this role ends on 12/31/26.
Work You’ll Do
Help build a research practice that extends tensor network methods beyond their established applications to address computational challenges in national security. You will work with researchers, engineers, and mission specialists to identify promising problems, develop new methods, and translate research into capabilities that can be evaluated and used.
Work with national security and domain specialists to translate mission challenges into mathematical models and computational problems. Potential research areas include uncertainty quantification, rare-event analysis, resilient infrastructure and supply chains, probabilistic inference, and dynamical systems.
Determine how dependencies, correlations, network topology, and tensor representations affect computational cost and accuracy. Identify when tensor network approaches are promising and where their limitations arise.
Design, implement, and optimize quantum-inspired algorithms, including tensor network, Pauli-propagation, dequantized, Ising, and QUBO-based methods, using high-performance computing and GPU resources where appropriate.
Collaborate with engineers to improve performance on CPU, GPU, and high-performance computing platforms.
Contribute technical expertise to government proposals and collaborations.
Move validated research from proof of concept to prototype to reusable product assets, including solver and simulator libraries, experiment frameworks, benchmarks, and engineering requirements, in partnership with product and engineering teams.
Serve as technical subject-matter expert in client discussions, executive briefings, proposals, demonstrations, and ecosystem collaborations, clearly communicating results, limitations, uncertainty, and risks.
Mentor researchers and engineers, provide constructive technical review, and establish standards for research rigor, reproducibility, software quality, and communication.
Support work involving government agencies, national laboratories, academic groups, vendors, and other clearance-sensitive stakeholders in accordance with applicable clearance and information-handling requirements.
Required Skills
Doctoral degree in Physics, Applied Mathematics, Computer Science, Quantum Information Science, Electrical Engineering, Operations Research, or a related field.
Possess or be willing to seek, obtain, and maintain a U.S. government security clearance.
5+ years of relevant research or development experience, including independently leading technically complex work from problem framing through analysis and communication of conclusions.
Expertise in tensor network methods such as matrix product state (MPS), density matrix renormalization group (DMRG), time-evolving block decimation (TEBD), projected entangled pair states (PEPS), tree tensor networks, or tensor train decompositions, including bond-dimension control, truncation-error analysis, and contraction-path optimization.
Strong foundation in numerical methods, optimization, randomized numerical linear algebra, and quantum-inspired methods for machine learning.
Ability to formulate real-world problems and assess when structural characteristics, such as low entanglement, low rank, sparsity, or operator locality make them suitable for quantum-inspired approaches.
Demonstrated ability to design fair and rigorous benchmarks using strong baselines, appropriate tuning, controlled compute budgets, transparent metrics, and honest reporting of positive and negative results.
Strong Python skills, with experience implementing, reproducing, or critically evaluating algorithms using scientific and quantum software such as NumPy, SciPy, JAX, PyTorch, Quimb, ITensor, Cotengra, Qiskit, Cirq, or PennyLane.
Ability to translate technical research into client-relevant insights, business value, prototypes, roadmaps, or offering priorities.
Publications, preprints, open-source contributions, community benchmarks, conference presentations, or other evidence of technical contribution in quantum-inspired computing, tensor networks, classical simulation, or optimization.
Strong written and verbal communication skills, including the ability to explain complex technical findings, uncertainty, tradeoffs, and recommendations to technical and business audiences.
Demonstrated ability to guide collaborators, provide constructive technical feedback, and work across research, engineering, product, and business teams.
Ability to travel up to 10%, based on business needs and the clients and industries served.
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
Preferred Skills
Research extending tensor networks to applications beyond quantum many-body physics, such as uncertainty quantification, numerical integration, probabilistic graphical models, stochastic processes, differential equations, optimization, or machine learning.
Experience developing new tensor representations, network architectures, contraction algorithms, or methods for controlling approximation error.
Expertise in one or more complementary areas, such as probability and statistics, stochastic modeling, dynamical systems, optimal control, numerical analysis, or computational physics.
Experience with GPU acceleration, parallel computing, or distributed scientific workloads, using tools such as JAX, PyTorch, CUDA, cuTensorNet, MPI, or related technologies.
Experience with scientific tensor software such as Quimb, ITensor, Cotengra, or comparable libraries.
Experience applying computational methods to national security problems, including infrastructure resilience, logistics and supply chains, sensing, materials, or modeling complex systems under uncertainty.
Experience collaborating with government agencies, national laboratories, academic researchers, or multidisciplinary research teams.
Experience developing research proposals, helping define a research agenda, or transitioning research software to broader use.
Familiarity with quantum algorithms or quantum simulation where relevant to the research.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 - $265,100.
