Ph.D on Quantum Machine Learning for Medical Imaging

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University College London - UCL
12 June, 2017


University College London London
United Kingdom
51° 30' 26.4636" N, 0° 7' 39.9288" W

PhD Projects on offer at UCL


Title: Quantum Machine Learning for Medical Imaging

Partner: Siemens

UCL co-supervisor: Dr Simone Severini

Main location of project: UCL

Theory or Experiment: Theory

Summary of research project:


Quantum machine learning (QML) is an emerging research field with the potential to revolutionize machine learning and artificial intelligence. It combines machine learning with quantum computers which have the ability to perform extremely fast calculations to solve problems that are computationally intractable with classical computers.


This PhD is in conjunction with the Medical Imaging Technology group at Siemens Healthcare. For 170 years Siemens has been pioneering technology to improve our lives. Today, Siemens products are used to diagnose and treat over 100 million people each year. Many of these products leverage the power of machine learning for a wide range of applications from early cancer detection to planning and guiding brain surgery. This unique PhD combines the cutting edge field of QML with the opportunity to impact and change the lives patients. The work will focus on developing new QML algorithms and exploring how these algorithms can be used to improve medical image analysis.



Industrial Track Doctoral StudentshipsApplications now open

UCL’s CDT in Delivering Quantum Technologies is pleased to announce, following receipt of additional funds from EPSRC and industrial partners, three new Industrial Track studentships. This is a new type of studentship on our programme which provides:


  • Fully funded 4-year studentships including fees, stipend and a generous training and research support package
  • Enhanced Stipend (£18,953 per year)
  • Innovative MRes in Quantum Technologies in first year of programme
  • PhD, in years 2-4, in collaboration with a world-class industrial partner
  • Open to UK residents and international students*.
  • Start date: 25th September 2017


These Industrial Track studentships, which are co-funded by an industrial partner, allow the student to select the specific theme of PhD project at the application stage (see project descriptions below). Note: Some PhD projects are embedded within the industrial partner lab, outside of UCL.


Applicants should have a strong academic track record (to Masters level) in Physics, Electrical Engineering, Chemistry Computer Science or Maths.


Applications are now open. To apply, please see our web-site:

Application Deadline: 12th June 2017


* There is a limited quota of studentships available for EU-fee and international-fee status students.


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