UK PhD Programme 2026

4 days ago


London, Greater London, United Kingdom Quantum Motion Technologies Full time
About The Role and Team

We are currently accepting applications for our PhD programme

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. The successful candidate is expected to start in early 2026.

Application Process:

  • 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.
If your application is successful, you will be invited to a 30-minute technical interview with the relevant team.

Our Team

Since 2021 our team has 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. Our founders are internationally renowned researchers from UCL and Oxford University who have pioneered the development of qubits and quantum computing architectures. Our chairman is the co-founder of Cadence and Synopsys, the two leading companies in the area of Electronic Design Automation. 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, Spain and Sydney, with our primary hub in Islington (London).

Functions of the Role

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.  

Partner Universities: University College London and University of Cambridge 

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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.

Partner University: University of Oxford 

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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. 

This PhD project focuses on furthering the detailed understanding of electron behaviour in silicon quantum dots and incorporating this into sophisticated models of qubit noise and error. The resulting models will be directly utilised by the Architectures team to inform system-level dynamics and quantum error correction strategies for the processor. This work sits at the intersection of cutting-edge semiconductor physics, open quantum systems theory, and quantum error correction.

Partner University: University College London, UK 

Experience - Essentials
  • Academic Qualification: Minimum 2.1 (or equivalent) Master's degree in the fields of Physics or Electrical Engineering or a closely related discipline studied to master's level. (The Architectures & Applications track typically requires a 1st Class degree strictly in Physics.)

  • Data Analysis & Reporting: Demonstrated ability to perform robust data analysis and preparation of clear technical reports and presentations.

  • Teamwork & Communication: Excellent communication skills and demonstrated experience of working collaboratively in a team environment.

  • Numerical Skills: Demonstrated numerical skills in programming (e.g., Python, C/C++, or Matlab).

Experience - Desirable

Please review the detailed requirements for each team via the PhD Opportunities page.

Benefits
  • Working with a World-Leading Team: Collaborate daily with world-leading experts in silicon spin qubits, cryogenic electronics, and scalable CMOS technology from both Quantum Motion and our academic partners.
  • Industrial Exposure: Gain crucial, hands-on experience through a dedicated industry placement at Quantum Motion, bridging fundamental science and commercial hardware development.
  • Cutting-Edge Facilities: Access and operate state-of-the-art laboratory equipment, including dilution refrigerators and advanced measurement platforms.
  • Skill Development: Develop highly marketable expertise at the intersection of quantum mechanics, semiconductor engineering, machine learning, and high-frequency electronics.
  • Dedicated Mentorship: Receive guidance from both an established academic supervisor and an industry expert throughout your research journey
  • Conference & Travel Budget: Receive a dedicated annual budget to support travel and attendance at quantum conferences and workshops 
  • Vibrant Ecosystem: Become part of the dynamic UK quantum technology ecosystem  
EEO Statement

Quantum Motion is a fast-growing quantum computing scale-up based in London founded by internationally renowned researchers from UCL and Oxford University with over 40 years' experience in developing qubits and quantum computing architectures. Bringing together state-of-the-art cryogenic facilities and an outstanding interdisciplinary team, we are developing quantum processors based on industrial-grade silicon chips, with the potential to radically transform computing power in areas such as materials modelling, medicine, artificial intelligence and more.



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