About the mission
We're looking for an experienced physicist to own the numerical simulation strategy for our superconducting qubits — setting direction, defining what counts as a trustworthy result, and identifying where our methods need to improve. This is a broad-expertise role spanning quantum physics, microwave engineering, and numerical methods: you don't need to be the top expert in each, but a deep understanding of each domain and how they intersect is required.
About the role
As technical lead for numerical simulation of superconducting qubits, you'll own how Alice & Bob predicts and validates device behavior before it reaches the lab. You'll define our simulation approach — from microwave design to qubit dynamics — and set the bar for when a result can be trusted. Where our methods fall short, you'll spot it and drive the fix. You're not executing someone else's roadmap; you're setting it, working closely with the physicists and engineers in the details.
About you
You have several years of experience beyond your PhD, with expertise spanning across quantum physics, microwave engineering, and numerical methods. You're comfortable challenging a result that doesn't hold up, backed by rigor rather than instinct, and you're motivated by owning a technical direction, not just contributing to one.
Responsibilities
- Own the predictive performance of our simulation stack end to end — accuracy, reliability, and efficiency from device physics through numerical implementation.
- Set the standard for what "trustworthy" means across microwave, quantum, and numerical simulations — defining accuracy, convergence, and validation practices, and leading the theoretical justification of our tools and methods.
- Find and fix what's holding the stack back, whether the bottleneck is performance, robustness, or model fidelity.
- Shape the roadmap for our simulation tools, working closely with domain experts across the company.
- Close the loop with experiment — validating simulations against measured device performance alongside experimentalists.
- Be the go-to authority on simulation methodology across the team.
Requirements
- 7+ years of post-PhD experience in a relevant academic field or industry.
- PhD or equivalent in quantum physics, applied physics, electrical engineering, quantum information, or computational physics.
- A proven track record of technical leadership: driving simulation or modeling methodology at the organizational level, with results that directly shaped device design decisions.
- Broad, hands-on mastery across the full simulation chain — from device physics to numerical implementation — with recognized, go-to depth in at least one of these areas.
- Deep experience simulating superconducting qubits or comparable systems: finite element methods (Ansys HFSS, COMSOL, Palace), circuit quantization (scQubits, Quantum Metal), and quantum simulation (QuTiP, Dynamiqs, CUDA-Q).
- Command of the underlying quantum physics: circuit QED, Hamiltonian modeling, open quantum systems, decoherence mechanisms, physical gates and measurement.
- Fluency in microwave engineering for quantum applications: passive components (resonators, transmission lines, filters, couplers, circulators), active devices (amplifiers, mixers), and measurement instrumentation (VNAs, spectrum analyzers, homodyne/heterodyne detection).
- Strong software engineering foundations for scientific computing — Python, NumPy/SciPy or JAX, and Git — sufficient to build and maintain simulation infrastructure others rely on.
- The judgment to determine when a simulation result can be trusted, and the standing to make that judgment hold across teams — even against pushback from domain experts.
- A track record of mentoring senior scientists and engineers, and building consensus among specialists who don't naturally agree.
- Hands-on experience with HPC or large-scale simulations.
- Publications in circuit QED or computational electromagnetics.
- Hands-on experience in experimental research, providing a practical sense of how quantum devices behave in the lab — beyond what models predict.
Nice to have
Recruitment Process
- Screening Call with Grace, Talent Acquisition Specialist (30 min)
- Hiring Manager Interview with Mattis (45 min)
- Technical Presentation with the Team (60 min)
- Leadership Team Interview (45 min)
- Fit Interview (45 min)
- Reference check
