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Analogue Designer, CMOS Modelling

Job in Oxford, Oxfordshire, OX1, England, UK
Listing for: Oxford Ionics
Full Time position
Listed on 2026-10-06
Job specializations:
  • Engineering
    Systems Engineer
Salary/Wage Range or Industry Benchmark: 90000 - 130000 GBP Yearly GBP 90000.00 130000.00 YEAR
Job Description & How to Apply Below

IonQ, Inc. [NYSE: IONQ] is the world’s leading quantum platform and merchant supplier - delivering integrated quantum solutions across computing, networking, sensing, and security. IonQ’s newest generation of quantum computers, the IonQ Tempo, is the latest in a line of cutting-edge systems that have been helping customers and partners including Amazon Web Services, and AstraZeneca achieve 20x performance results and accelerate innovation in drug discovery, materials science, financial modeling, logistics, cybersecurity, and defense.

In 2025, the company achieved 99.99% two-qubit gate fidelity, setting a world record in quantum computing performance.

Oxford Ionics, now part of IonQ, is pioneering the next generation of quantum computing. Using our world-leading trapped-ion technology, we’re building the most powerful, accurate and reliable quantum systems to tackle problems that today’s supercomputers cannot solve. Joining Oxford Ionics means becoming part of a global IonQ team that is transforming the future of quantum technology - faster, at scale, and with real world impact.

Headquartered in College Park, Maryland, IonQ has operations in California, Colorado, Massachusetts, Tennessee, Washington, Italy, South Korea, Sweden, Switzerland, Canada, and the United Kingdom. Our quantum computing services are available through all major cloud providers, while we also meet the needs of networking and sensing customers across land, sea, air, and space. IonQ is making quantum platforms more accessible and impactful than ever before.

What

to expect:

We are looking for a Analogue Designer, CMOS Modelling to join our Cryo-CMOS IC team at IonQ based in our Oxford office. In this role, you will be responsible for owning full-chip mixed-signal CMOS modelling as a first-class part of our Cryo-CMOS development flow. This includes building the behavioural model of the chip that the whole team will simulate against, allowing the team to design, verify and validate the integrated circuits that control our quantum processors - the novel technology that sits at the very heart of our world-leading quantum computers.

You will enable the team to work in conditions from room temperature down to a few kelvin. This work will allow the team to meet our research and development goals, contributing directly to our ability to deliver on our technological milestones.

In this role you’ll play an important part in shaping the modelling methodology, standards and sign-off criteria that support our work in building the world’s most advanced quantum systems.

What you'll be responsible for:

In this position, you will work on deriving behavioural models from first-principles mathematics to support the delivery of cryo-CMOS ASICS for our trapped-ion quantum processors. You will implement these models in Verliog-A, Verliog-AMS and real-number models, and correlate these against schematic and measured silicon. You will have the opportunity to set modelling standards across the whole team, raising the bar of quality so models can be used to inform and drive tapeout decisions.

In turn this will raise the modelling capability of the engineers around you, contributing directly to the success of IonQ's quantum computing roadmap.

  • Own the full-chip modelling strategy, including model architecture, abstraction levels, accuracy targets and sign-off criteria, and implementing across the whole IC development flow
  • Develop Verilog-A and Verilog-AMS models of analogue blocks (references, DACs, switches, regulators, clock distribution) and assemble them into a simulatable full chip
  • Build real-number models (System Verilog nettype/UDN, legacy wreal) so the full chip runs in digital verification and regression at speed
  • Derive models from…
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