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- Posted on 29th May 2018

Ph.D. in Interactive Machine Learning for Medical Image Segmentation


Location: Oxford, UK

Salary: Approximately, £35k p.a.

Living, mobility, and family allowances are determined by the EU and are subject to exchange rate.

Contract: 3-year fixed term. You will be a full-time employee of Mirada Medical during your studies.

To Apply: Please forward CV & covering letter to by 15th of August 2018.

Mirada Medical ( and the University of Oxford are seeking a Ph.D. student as part of the PREDICT Innovate Training Network research programme.

The Project 

Research is often focused on automatic tools to segment images; however, these tools often do not work well outside of a narrow range of conditions. In this project, a semi-automatic approach for tumour segmentation will be developed, intended to be as broadly applicable as possible. From a technical point of view, the investigation will consider the integration of user-interaction within radiomics and machine learning approaches.

This project will be conducted at Mirada Medical Ltd, in collaboration with the BUBBL group at the University of Oxford. Secondments to other partners within the European consortium will be required during the project.

About Mirada

Mirada’s history can be traced back to 1998 when Oxford University spun out companies with technologies in image registration, tracking and mammography. Mirada went on to establish itself as a world-class technology provider in the area of multi-modality medical imaging. Mirada was ultimately acquired by PET scanner manufacturer, CTI, which in turn was acquired by Siemens. In late 2008, Mirada became a fully independent company again, still developing world-class medical imaging software. The company has been growing rapidly through-out the economic downturn and is continuing its expansion.

Located at the centre of the beautiful city of Oxford, UK, Mirada participates in collaborative research projects across numerous University departments. Mirada also has strong links to other leading research and clinical facilities worldwide.

Science and Medical Technology Group

The Science and Medical Technology group is at the heart of new developments within the company. Our research interests include registration, analysis of multi-modality imaging and advanced quantification of images.

Description & Requirements                    

Essential Skills

  • a MSc (or equivalent) in a mathematical discipline, ideally in biomedical engineering or image processing
  • Good coding skills
  • Have excellent communication skills
  • Readiness to travel Europe for a longer duration
  • Fluent in English, both written and spoken

Advantageous Experience

  • Machine learning / Deep learning
  • Medical imaging
  • Image segmentation
  • Matlab
  • C++
  • Python
  • Tensorflow


  • This position has the following conditions placed on it under the rules for the Innovative Training Network (the funding scheme). The Early Stage Researcher (ESR):
  • Must not have resided or carried out their make activity (work, study etc) in the UK for more than 12 months in the 3 years immediately starting work with Mirada.
  • Must be in the first four years of their research career
  • Must not have been awarded a doctoral degree

Company Culture

Mirada Medical values staff as the company’s greatest asset.  Our objective is to deliver exceptional products and service to our customers; we recognise that every member of Mirada helps make this possible. Diversity and individuality are celebrated qualities in our workplace. Innovation and inspiration are encouraged and supported with autonomy and teamwork.

Benefits Policy

Mirada strives to offer a first-class benefits package to all employees and to make the company an attractive place to work. Through innovative means, we seek to offer rewards that are usually only viable for larger organisations.

Available Benefits

  • 25 days annual leave plus 8 paid bank holidays
  • 3% company contribution-matching pension
  • Flexible working hours
  • Opportunity to buy or sell annual leave
  • Cycle to Work scheme
  • Childcare vouchers
  • Refreshments provided