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Interpretation of Features in Biological Images

  • Full or part time
  • Application Deadline
    Wednesday, September 30, 2020
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

About This PhD Project

Project Description

We are seeking applicants with an interest in data analysis and programming to develop methods to extract information from high resolution images of metals in tissue.

There is a growing demand for methods that provide rapid imaging of metals in biological tissue. Application areas include medical diagnosis, toxicology, drug development and oncology. In collaboration with industry, Loughborough University have developed a world leading system for imaging metals, which is based on laser ablation – inductively coupled plasma – mass spectrometry (LA-ICP-MS). With its high speed, high sensitivity and sub-micron spatial resolution, the prototype system is ideally placed to image small structural features and/or potential anomalies in tissue.

Development of this technology is producing ever larger and more complex data sets, with in excess of half a million data points now generated for every minute of analysis. Processing and interpreting such large volumes of data is now becoming a bottleneck in the imaging process that must be tackled before full clinical implementation of the technology can be achieved. This project will therefore aim to develop statistical protocols and image analysis techniques that will recognise, extract and interpret relevant information from high-resolution images acquired using LA-ICP-MS.

Entry requirements

The successful applicant will have an interest in both the analytical and programming aspects of the project and will demonstrate a willingness to engage in interdisciplinary collaboration with industrial and clinical partners, as appropriate.

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Chemistry, Physics, Maths, Computer Science or a related scientific discipline. A relevant Master's degree and / or experience in one or more of the following will be an advantage: analytical science, data analysis, programming using Python or C++.

How to apply

All applications should be made online at

Under school/department name, select 'Chemistry'.

Please quote reference CM/AJM-Un1/2020. The deadline for applications is 30 September 2020.

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