This is a unique opportunity to work at the cutting edge of technology development, developing new innovative circuits, devices and theoretical methods to tackle the engineering challenges of implementing a large-scale quantum computer in silicon. PhD students will gain research and industrial experience working with some of the brightest quantum engineers, IC engineers and quantum computing theoreticians in a fast-growing research and development environment. We do not award PhDs, and any offer for a PhD will be done in conjunction with one of our partner universities. Quantum Motion will support you and provide guidance on your university application. Quantum Motion has partnerships and works collaboratively with many leading universities in the UK, Europe, the US and Australia.

See below for details on what opportunities we offer in each location. We offer the opportunity to carry out PhD research across 4 Quantum Motion teams:

• Quantum Hardware
• Architectures and Applications
• Device Modelling
• Intelligent Automation

How to apply:

Please submit your application directly to the relevant team by clicking the corresponding links below. You will be required to attach the following documents:

• CV
• 1 page personal statement which describes your motivation for pursuing a PhD and explains which topics are of interest to you (in order of preference) and why.

Deadlines:

Applications aligned with university deadlines for 2026 are now closed. We plan to reopen the application process in mid-late 2026 and encourage interested candidates to monitor this page

However, we remain open to hearing from exceptional candidates who believe their research interests strongly align with our work. Where there is a clear fit, we are happy to explore potential PhD opportunities outside the standard cycle.

If you would like to be considered, please email phd-applicants@quantummotion.tech with your CV and a brief outline of your proposed research interests.

Due to the volume of enquiries we receive, we will only be in touch if your profile is closely aligned with our current research priorities.

Quantum Hardware

Partner Universities: UCL, UK | University of Cambridge, UK | University of the Basque Country, Spain | UTS (Sydney Quantum Academy), Australia

The Quantum Hardware Team at Quantum Motion specialises in designing, validating and operating quantum processors based on silicon (CMOS) industrial technology. This PhD track is experimental in nature with laboratory based work. Silicon-based approaches to quantum computing offer advantages such as high qubit density, record qubit coherence lifetimes for the solid state, and the ability to leverage the advanced nanofabrication methods of CMOS technologies. Two-qubit gate fidelities for spin qubits in silicon now exceed 99.5% and registers of up to 6 qubits have been made so far. By integrating CMOS quantum devices on-chip with ‘classical’ digital and analogue electronics, arrays of up to 1024 quantum dots have been addressed and rapidly characterised in just 5 minutes. These advances open up many exciting research opportunities for spin-qubits based on silicon MOS (metal-oxide-semiconductor) devices, fabricated using the same processes used routinely across the IC industry today.

Possible research paths:

• Working with the Quantum Hardware team to measure qubit properties such as single- and multi- qubit gate fidelities, understand their relation to device design, and help validate and refine fault-tolerant architectures based on spin qubits in silicon
• Working with Quantum Motion’s IC team on the design and test of CMOS circuits and devices at cryogenic temperatures – for this project, experience in device validation and/or analogue circuit design would be beneficial
• Working with the Intelligent Automation team on the automated tune-up of quantum dots in multi-gate quantum dot arrays – for this, a basic understanding of machine learning techniques would be helpful

Skills and experience:

• Minimum 2.1 (or equivalent) Master’s degree in the fields of Physics or Electrical Engineering or closely related discipline studied to master’s level
• Particular experience of relevance will depend on the direction the student would like to take in the PhD project – understanding and/or experience in at least one of the following topics would be beneficial: quantum computing, measuring quantum devices, cryogenic measurements, analogue circuit design, machine learning, microwave engineering
• Experience of working in a laboratory environment
• Demonstrated ability to perform experiments, data analysis and preparation of technical reports and presentations
• Knowledge of scripted data acquisition software, such as Python or Matlab
• Excellent communication skills and demonstrated experience of working collaboratively in a team environment

Applications for our Australian PhD cohort have now closed.

Architectures and Applications

Partner University: University of Oxford, UK

The Architectures and Applications Team at Quantum Motion specialises in quantum algorithms and computing architectures. The team considers how to optimise silicon qubit architectures in order to run particular quantum algorithms of interest. Building quantum computers means learning to control qubits. The first generation of quantum computers will be imperfect, by comparison to our reliable conventional technologies, but they will still have the potential to be vastly more powerful. Therefore there is great interest in finding the potential useful applications of such systems. Theory projects will use both analytic techniques and conventional supercomputers to understand the behaviour of quantum computers including their limitations and flaws. A current focus is to identify applications, such as novel materials and chemistry discovery, which may be able to run successfully on a near-term quantum computer despite its imperfections. We need to map the detailed architectures and error models to the desired application through error mitigation protocols.

More information can be found at Professor Simon Benjamin’s ongoing quantum technologies theory group.

Skills and experience:

• Minimum 1 (or equivalent) Master’s degree in Physics
• Competence in mathematics for physics and analytic techniques with modules in theoretical physics an advantage
• Understanding of the physics of semiconductors and spins
• Numerical skills in programming
• Concepts related to machine learning and optimisation may be useful and a prior experience here could be valuable
• An interest in quantum algorithms and understanding their properties will also be important
• Demonstrated ability to perform data analysis and preparation of technical reports and presentations
• Proficiency in Python and/or C/C++
• Knowledge of scripted data acquisition software, such as Matlab
• Demonstrated understanding of software best practices, including unit and integration testing
• Excellent communication skills and demonstrated experience of working collaboratively in a team environment

Applications for our UK PhD cohort are now closed in line with university deadlines. We may consider exceptional candidates outside of the hiring cycle where there is a strong research fit. If you would like to be considered, please email phd-applicants@quantummotion.tech with your CV and a brief outline of your research interests.

Device Modelling

Partner University: UCL, UK

The Device Modelling team at Quantum Motion studies how detailed designs of silicon structures can be used to provide predictions in terms of qubits, gate fidelities and errors. Their aim is to build predictive modelling capabilities that give rapid feedback on the quantum performance of candidate quantum circuit designs. Skills and experience:

• Minimum 2.1 (or equivalent) Master’s degree in the fields of Physics or Electrical Engineering or closely related discipline studied to master’s level
• Competence in mathematics for physics and analytic techniques with modules in theoretical physics an advantage
• Understanding of the physics of semiconductors and spins
• Numerical skills in programming
• Concepts related to machine learning and optimisation may be useful and a prior experience here could be valuable
• Demonstrated ability to perform data analysis and preparation of technical reports and presentations
• Proficiency in Python and/or C/C++
• Knowledge of scripted data acquisition software, such as Matlab
• Demonstrated understanding of software best practices, including unit and integration testing
• Excellent communication skills and demonstrated experience of working collaboratively in a team environment

Applications for the Device Modelling team have now closed. We plan to re-open the application process in late-2026 and encourage interested candidates to monitor this page.

About Us

Since 2021 we have been listed every year in the “Top 100 Startups Worth Watching” in the EE Times, and our technology breakthroughs have been featured in The Telegraph, BBC and the New Statesman. We’re backed by a team of top-tier investors including Bosch Ventures, Porsche SE, Sony Innovation Fund, Oxford Sciences Innovations, INKEF Capital and Octopus Ventures, and we have so far raised over £62 million in equity and grant funding. We bring together the brightest quantum engineers, integrated circuit (IC) engineers, quantum computing theoreticians and software engineers to create a unique, world-leading team, working together closely to maximise our combined expertise. Our collaborative and interdisciplinary culture is an ideal fit for anyone who thrives in a cutting-edge research and development environment focused on tackling big challenges and contributing to the development of scalable quantum computers based on silicon technology. 

Our team of 100+ is based across London, Oxford, San Sebastián and Sydney, with our primary hub in Islington (London).