PhD Studentship Histopathology Image Understanding and Machine Learning for Cancer Research

Applications are invited for one PhD studentship starting in January 2014. The focus of this doctoral research project is on machine learning and image analysis for histopathology image understanding in liver cancer cases. The objective is to use image processing techniques in assessment of tumour regression.

The studentship will be based in the School of Electronic Engineering and Computer Science (EECS) at Queen Mary University of London, in the Multimedia and Vision Research Group. The project undertaken under this studentship is expected to fit into the wider research programme of the group, which has widespread recognition for its research in image processing and computer vision areas.

This studentship, funded by the School of Electronic Engineering and Computer Science, is for 3 years and will cover student fees and a tax-free stipend starting at £15,726 per annum. Due to funding applicants must be UK or EU nationals or residents as defined here: Candidates should have a first class honours degree or equivalent, or a strong Masters Degree, in computer science, mathematics, biology or electronic engineering. Please contact Dr Qianni Zhang ( if you would like to know more details, or have any queries about how to apply.  

To apply, please follow the on-line process (see the apply button below) by selecting “Electronic Engineering ” in the “A-Z list of research opportunities” and following the instructions on the right hand side of the web page. 

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Please note that instead of the ‘Research Proposal’ we request a ‘Statement of Research Interests’. Your Statement of Research Interest should answer two questions: (i) Why are you interested in the proposed area?  (ii) What is your experience in the proposed area? Your statement should be brief: no more than 500 words or one side of A4 paper. Mark clearly the statement with Your Name and the title “histopathology image understanding and machine learning for cancer research”.  In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper. More details can be found at:

The closing date for the applications is 30 November 2013.    

Interviews are expected to take place in December 2013.

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