Build practical quantum cryptanalysis

Lead the scientific program connecting elliptic-curve arithmetic to practical quantum cryptanalysis.

Responsibilities

Set research priorities and evaluation criteria. Lead researchers working on reversible arithmetic and cryptanalytic algorithms. Connect logical improvements to compilation and fault-tolerance constraints. Review consequential claims and help define responsible research boundaries.

Relevant experience

A strong research record in quantum algorithms, cryptanalysis, or fault-tolerant computation, together with the ability to lead a rigorous research program across specialties.

Evidence to share

Publications or technical work showing both an original contribution and careful treatment of assumptions.

Develop and evaluate the algorithmic components required for elliptic-curve quantum cryptanalysis.

Responsibilities

Study arithmetic constructions and algorithmic tradeoffs. Produce reproducible experiments and explicit resource estimates. Investigate how improvements compose into larger workloads. Work with verification and compilation specialists to test the significance of a result.

Relevant experience

Quantum algorithms, computational number theory, cryptography, or closely related research with strong mathematical and programming skills.

Evidence to share

A paper, implementation, or technical note explaining a difficult algorithm and its limitations.

Turn arithmetic designs into reliable and measurable circuit implementations.

Responsibilities

Implement arithmetic kernels. Optimize logical resources under consistent accounting. Maintain tests and experiment records. Investigate the effects of ancilla management and circuit composition without treating a smaller isolated kernel as proof of a better full computation.

Relevant experience

Reversible circuits, compiler optimization, cryptographic arithmetic, or performance-sensitive numerical software.

Evidence to share

An implementation with correctness checks and an explained performance tradeoff.

Establish confidence that research improvements preserve the required computation.

Responsibilities

Design validation strategies for circuits and composed workloads. Investigate where simulation and sampling are sufficient and where stronger arguments are needed. Build counterexample-driven tests. Audit evaluation tools for shortcuts, false positives, and inconsistent assumptions.

Relevant experience

Formal methods, quantum verification, programming-language semantics, or rigorous testing of mathematical software.

Evidence to share

A verification result, proof tool, or example of finding an error that ordinary testing missed.

Connect logical circuit research to plausible fault-tolerant execution.

Responsibilities

Investigate error-correction and execution assumptions. Model the cost of non-Clifford operations and supporting resources. Study reliability, syndrome extraction, decoding latency, and scheduling tradeoffs where relevant to the target architecture. Work with hardware teams to identify where abstract assumptions fail to match available interfaces or devices.

Relevant experience

Quantum error correction, fault-tolerant architectures, decoding, or related systems research.

Evidence to share

Work that connects a theoretical construction to realistic operating assumptions.

Make resource and runtime claims comparable and inspectable.

Responsibilities

Develop transparent estimation models. Quantify sensitivity to architectural and error assumptions. Distinguish logical from physical resources and estimates from measurements. Help develop the proposed Maximum Reliable Kernel framework and its reporting conventions.

Relevant experience

Resource estimation, quantum architecture, simulation, statistical modelling, or performance analysis.

Evidence to share

A model or benchmark with reproducible inputs and a clear account of uncertainty.

Translate cryptanalytic workloads into executable representations for target platforms.

Responsibilities

Build and evaluate compilation passes. Work on intermediate representations and resource accounting. Integrate specialized external tooling where it is stronger than an internal implementation. Preserve correctness and traceability across transformations.

Relevant experience

Compiler engineering, intermediate representations, optimization, quantum programming tools, or systems programming.

Evidence to share

Compiler contributions or an optimization whose correctness and effect you can explain.

Study how finite hardware resources change the execution of a cryptanalytic workload.

Responsibilities

Develop mapping and scheduling approaches for target constraints. Measure resource contention and runtime effects. Compare alternatives under explicit assumptions. Work with fault-tolerance and provider-integration teams to keep models tied to plausible execution.

Relevant experience

Scheduling, combinatorial optimization, quantum compilation, distributed systems, or resource-constrained execution.

Evidence to share

A scheduling or systems project that demonstrates useful tradeoff analysis.

Build the technical relationships and interfaces needed to run Potomac software on external quantum hardware.

Responsibilities

Scope joint experiments and compute requirements. Understand provider interfaces and access conditions, including runtime, feedback, and control interfaces where available. Lead integration planning across architectures and specialized software providers. Translate device constraints into research priorities and report what each integration actually supports.

Relevant experience

Quantum platform engineering, experimental systems, provider SDKs, or technical leadership connecting research software to devices.

Evidence to share

A project that moved beyond simulation into an external platform or experimental environment.

Run carefully scoped experiments and explain the difference between a planned workload and an observed result.

Responsibilities

Prepare approved jobs, collect experiment metadata, and analyze reliability. Coordinate with provider teams. Investigate noise and execution limitations. Maintain reproducible records and help select useful next experiments.

Relevant experience

Experimental quantum computing, scientific instrumentation, platform benchmarking, or comparable research engineering.

Evidence to share

An experiment report that makes its setup, limitations, and results independently understandable.

Provide the reliable computing foundation for the research organization.

Responsibilities

Develop job scheduling, artifact storage, observability, reproducible environments, and compute-cost accounting. Support researchers across CPU, accelerator, simulator, and external quantum resources. Keep research systems secure and maintainable as the program grows.

Relevant experience

Distributed systems, scientific computing infrastructure, platform engineering, or high-performance computing.

Evidence to share

Infrastructure that enabled a team to run demanding experiments reliably.

Investigate how frontier models can contribute to difficult quantum-software research.

Responsibilities

Design and evaluate model-assisted search strategies. Compare performance against explicit baselines and compute budgets. Study when multiple candidates or research agents improve outcomes. Analyze failure modes rather than relying on attractive model explanations.

Relevant experience

AI agents, program synthesis, search, evaluation, optimization, or machine learning applied to scientific work.

Evidence to share

A result that demonstrates an improvement under a clear evaluation protocol.

Build the execution systems that make model-driven experiments reproducible and controllable.

Responsibilities

Implement task orchestration, bounded tool access, experiment isolation, checkpoints, and result capture. Support parallel exploration and evaluation. Make research runs inspectable and recoverable when jobs fail. Integrate models without tying the research process to one provider.

Relevant experience

Agent infrastructure, distributed execution, developer tooling, or reliable systems for automated experimentation.

Evidence to share

An execution system whose failures and resource use can be understood from its records.

Ensure that a better benchmark score represents a meaningful improvement.

Responsibilities

Build evaluators and comparable baselines. Detect invalid outputs and evaluator exploitation. Maintain experiment provenance and reproducibility. Work with domain researchers on correctness criteria and with AI researchers on ablations and cost measurements.

Relevant experience

Evaluation systems, testing, benchmarking, scientific software, or adversarial analysis of automated workflows.

Evidence to share

An evaluation design that changed the interpretation of a claimed result.

Turn the recovery-and-return ambition into a credible governance framework before consequential operations begin.

Responsibilities

Develop authorization and claims-review processes. Shape coordinated disclosure, access restrictions, incident handling, and conflict-of-interest controls. Work with technical specialists and appropriate external advisers on custody, return, and disputed claims. Maintain a clear distinction between proposed policy and adopted practice.

Relevant experience

Cryptographic security, vulnerability coordination, digital-asset custody, research governance, or related work with consequential technical systems.

Evidence to share

A policy or operating process that handled a difficult technical or institutional tradeoff.