Deadline

Value of Scholarship

Level of Study

Country Tenable

Renewable

No

Faculty of Medicine, Dentistry & Health & Faculty of Engineering

Supervisors: Dr Simon Johnston and Prof Alejandro Frangi

Project:

Infectious and inflammatory diseases together are responsible for a large proportion of human mortality and morbidity. Infectious diseases account for 25% of all deaths, are the biggest cause of death in the young and the leading cause of death in low-income countries. The inflammatory disease COPD is the 5^th biggest killer world-wide and is predicted to rise to 3^rd by 2030.  A major barrier in improving patient outcome in these diseases has been the failure to successfully transfer knowledge gained in research laboratories into medical treatments. Much of this failure is due to inadequate models of disease and new models are needed to close the gaps in our understanding and find new therapies.

Light microscopy is a particularly flexible and data rich approach but it is often difficult to extract quantitative data, manipulate and analyse large raw data sets. The aim of this PhD is to develop and use such tools and infrastructure for automated image analysis for quantitation of our zebrafish infection and immune models. Algorithms will be developed to automatically capture, normalize, map and statistically assess quantitative image-based phenotypes. Methods will also be developed for tracking specific cells, and recover statistical models of their dynamic interactions that could become the basis of developing mechanistic models of disease.

This PhD project will build on the use of infection and immune disease models and live light microscopy in the Johnston lab with the biomedical image computing expertise of the Frangi lab. You will be cross-trained in the laboratory techniques required for biomedical aspects of the project as well as developing the image processing, analysis and modelling required to enable automated quantitative data collection for studying infection and immune diseases. This project is ideal for a candidate with strong interest interdisciplinary training in both computational and experimental domains and will require use of both laboratory skills and algorithmic programming in C++.

Entry Requirements:

Candidates must have a first or upper second class honors degree or significant research experience preferably with majors in Computer Science, Engineering, Physics or Mathematics. Alternative, candidates with a major in Biomedical Sciences and a strong scientific programming track record in C++ will be welcome. Funding for stipend and UK/EU fees are available for UK/EU students only. Students applying from outside the UK/EU countries should have additional funding to cover the additional cost up to overseas fees.

Enquiries:

Interested candidates should in the first instance contact:

Simon Johnston (s.a.johnston@sheffield.ac.uk) or Alejandro Frangi (a.frangi@sheffield.ac.uk).

How to apply:

Please complete a University Postgraduate Research Application form and attach at least two references to your application.  To complete the application form please click on the ‘Apply’ button below.

Please clearly state the prospective main supervisor in the respective box and select ‘Medicine’ as the department.

Website: www.shef.ac.uk/medicine/infectionandimmunity

Closing date: 19^th July 2013

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