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Senior Research Fellow in Machine Learning for Computer Vision
  • Machine Learning
  • Database
  • Deep Learning
University of Warwick
University of Warwick
182 days ago

Full time (36.5 hours per week) Fixed term contract until 31 October 2022.

As Senior Research Fellow at the University of Warwick, you will lead the research into machine learning technologies for computer vision on a groundbreaking project funded by Cancer Research UK to develop artificial intelligence (AI) algorithms based on digital mammograms. The project is in partnership with the Centre for Cancer Prevention, located in Central London, and several collaborators in Europe and the USA.

There are increasing moves to replace one-size-fits-all mammography screening for breast cancer by risk-adapted screening, in which both the frequency with which women are screened and the modality are chosen based on risk of breast cancer. The aim of this project is to develop an artificial intelligence system to aid risk-stratified screening, by assessing risk of cancer at screening (detection), risk of masking due to breast density (false negative), and long-term risk of breast cancer following a negative screen. This will be done by using information from a very large repository of digital mammograms (breast x-ray).

As well as curating the mammogram database, you will also coordinate an extensive external validation exercise, where algorithms developed during the project will be compared head-to-head with those from collaborators and elsewhere.

The project is based at the Data Science & AI Group at WMG within the University of Warwick, where you will join a team of over 20 reseachers specialised in data science and statistical machine learning working at the interface between academia and industry.

At WMG we are committed to supporting staff to achieve their potential. We currently hold the Athena SWAN Bronze Award and the University of Warwick holds an Institutional Silver Award: a national initiative that recognizes the advancement of gender equality, representation, progression and success for all in academia. We are supportive of staff with caring responsibilities including a generous maternity/paternity/adoption/parental leave policy, and onsite childcare facilities. We will consider applications for employment on a part-time or other flexible working basis, even where a position is advertised as full-time, unless there are operational or other objective reasons why it is not possible to do so.

For an informal conversation about this role, please contact Professor Giovanni Montana (

Job Description


You will undertake research on this Cancer Research UK funded project, and develop artificial intelligence (AI) algorithms based on digital mammograms. The algorithms will be used for residual lifetime risk modelling of breast cancer in women who are found to be without breast cancer at their mammography screening visit. You will also develop AI algorithms to identify which mammograms are at a higher risk of failure of the screening test due to masking of the cancer from mammographic density, and help externally validate these algorithms. You will assist the Project Directors (Prof Montana at Warwick and Dr Adam Brentnall at Queen Mary University) in the successful execution of the project. For this position, the candidate is expected to contribute in the areas of statistical machine learning and computer vision.


Research and Scholarship

1. To adhere to information governance regulations and standards.

2. To assist in the curation of a large database of mammograms.

3. To develop novel deep learning methodologies for computer vision trained on the mammography datasets.

4. To work in collaboration with our partners and collaborators to ensure that the resulting machine learning algorithms are well integrated and implemented in a single piece of software.

5. Establish a sound research base within the department in order to develop research objectives, projects and proposals.

6. Identify sources of funding and contribute to the process of securing funds to support a developing research agenda.

7. Extend, transform and apply knowledge acquired from scholarship to research and appropriate external activities.

8. Write or contribute to publications or disseminate research findings using other appropriate media.

9. Make presentations at conferences or exhibit work in other appropriate events.

10. Routinely communicate complex and conceptual ideas to those with limited knowledge and understanding as well as to peers using high level skills and a range of media.

Teaching and Learning Support

1. Could be expected to contribute to the teaching and learning programmes in the department.

2. May be expected to supervise postgraduate research students.

3. May be involved in the assessment of student knowledge.

Administration and Other Activities

1. Collaborate actively within and out side of the institution to complete research projects and advance thinking.

2. Undertake specific departmental roles as may be required.

3. May be required to attend departmental meetings and to participate (where necessary) in other committees and working groups within the department, the faculty and the University.

4. Participate in relevant professional activities.

5. Ensure compliance with health and safety in all aspects of work and, when appropriate, undertake risk assessments.

6. Participate in and develop external networks, for example to identify sources of funding, generate income, obtain projects, or build relationships for future activities.

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