Radio-frequency Image Processing (EPSRC CDT in Distributed Algorithms)


Please note this opportunity is only available to UK students.  

This studentship has been developed by the University of Liverpool and STFC’s Hartree centre in partnership with Leonardo.

This PhD will develop novel methods for processing modern radar range-Doppler data, using methods taken from image processing and adapting them for use to process very large 2D signal data. The techniques will be required to adapt to the statistical properties of the radar data, which are normally very different to standard image data.

Traditional coherent radar processing forms a range-Doppler map and then applies techniques developed for earlier non-coherent radars using envelope detectors with a Constant False Alarm Rate (CFAR) filter applied. This usually involves throwing away anything which is not a point target – clutter, interfering signals etc. A more modern approach would be to treat the range-Doppler map as a radar “image” and apply image processing methods to it which extracts all the information and uses it to better effect (e.g. do active detection of targets and passive detection of emitters in the same process) and apply correlation between successive images also.

The key challenge is the associated increase in processing power required to apply advanced image processing techniques to very large images in real time. The non-academic partner (Leonardo) will be involved in defining the problem set and will help by supplying representative data for algorithm development and testing.

This project is part of the EPSRC Funded CDT in Distributed Algorithms: The What, How and where of Next-Generation Data Science.

The University of Liverpool is working in partnership with the STFC Hartree Centre and other industrial partners from the manufacturing, defence and security sectors to provide a 4 year innovative PhD training course that will equip over 60 students with the essential skills needed to become future leaders in data science, be it in academia or industry.

Every project within the centre is offered in collaboration with an Industrial partner who as well as providing co-supervision will also offer the unique opportunity for students to access state of the art computing platforms, work on real world problems, benchmarking and data. Our graduates will gain unparalleled experiences working across academic disciplines in highly sought-after topic areas, answering industry need.

As well as learning from academic and industrial world leaders, the centre has a dedicated programme of interdisciplinary research training including the opportunity to undertake modules at the global pinnacle of Data science teaching.  A large number of events and training sessions are undertaken as a cohort of PhD students, allowing you to build personal and professional relationships that we hope will lead to research collaboration either now or in your future.

The learning nurtured at this centre will be based upon anticipation of the hardware recourses arriving on desks of students after they graduate, rather than the hardware available today.

For informal enquires please contact Dr Ke Chen or

To apply for this Studentship please submit an application for a Maths PhD via our online platform ( and provide the studentship title and supervisor details when prompted. Should you wish to apply for more than one project, please provide a ranked list of those you are interested in.

For a full list of the entry criteria and a recruitment timeline (including interview dates etc), Please see our website 


Open to EU/UK applicants

Funding information

Funded studentship

This project is a fully funded Studentship for 4 years in total and will provide UK/EU tuition fees and maintenance at the UKRI Doctoral Stipend rate (£15,009 per annum, 2019/20 rate).