Super-resolution microscopy is an emerging field that tries to overcome the resolution limit of conventional microscopy. This project will take a multi-disciplinary approach to this problem by combining the fields of image processing with microscopy imaging to develop a novel super-resolution restoration method. Our research group has recently been developing such a super-resolution imaging technique, called translation microscopy (TRAM), in which a super-resolution image can be restored from multiple diffraction-limited (low resolution) images recorded from standard microscopes. This is basically an inverse problem, which retrieves high resolution images from diffraction-limited observations. It is solved by the model-based approach, referred to as image restoration. Our preliminary results have demonstrated that TRAM is capable of improving lateral resolution by 7-fold, delivering a multi-colour image with ~30nm resolution [see our recent publication: Zhen Qiu, et al, Translation Microscopy (TRAM) for super-resolution imaging, Scientific Report 6, Article number: 19993 (2016)].
This project aims to further develop this methodology, delivering a completely novel software application that would for the first time enable quantitative multi-colour super-resolution imaging. In this project we are particularly interested in its application to cancer imaging deep in living tissue. This work, in collaboration with biologic and biomedical colleagues, aims to improve our understanding on how cells behave in their natural environment, and quantifying changes in cell behaviour and the underlying mechanisms that mediate the changes. Furthered development of the TRAM methodology for cancer imaging has the potential to transform pre-clinical in vivo cancer research.
Supervisor: Weiping Lu, [email protected]
The Institute of Biological Chemistry, Biophysics and Bioengineering (IB3) is an excellent environment for PhD research. The institute applies advances in the chemical, physical, and engineering sciences to enable and enhance life science research. The interdisciplinary research interests and state-of-the-art facilities provide a unique environment for integrative research.
We aim to maintain a world-leading centre of excellence, building on a strong foundation of genuine inter-disciplinary research, a strong and diverse funding record and an extensive extra-mural collaborative network.
The candidate should have a good honours degree (1st or upper 2nd class, or equivalent) in mathematics, physics, computer sciences or engineering and a strong desire to develop his/her research career in image processing and analysis particularly for biological and biomedical applications. Previous research experience in medical imaging or a postgraduate degree in image processing will be an advantage but not essential. A successful candidate must have a strong interest in multi-disciplinary researches.
All applicants must have or expect to have a 1st class MChem, MPhys, MSci, MEng or equivalent degree by Autumn 2018. Selection will be based on academic excellence and research potential, and all short-listed applicants will be interviewed (in person or by Skype). DTP’s are only open to UK/EU applicants.
All applications must be received by Wedesday 31st January 2018. All successful candidates must commence studies by Saturday 1st December 2018 at the very latest.
How to Apply
Apply Online: https://hwacuk.elluciancrmrecruit.com/Admissions/Pages/Login.aspx
When applying through the Heriot-Watt on-line system please ensure you provide the following information:
(a) in ‘Study Option’
You will need to select ‘Edinburgh’ and ‘Postgraduate Research’. ‘Programme’ presents you with a drop-down menu. Choose Chemistry PhD, Physics PhD, Chemical Engineering PhD, Mechanical Engineering PhD or Electrical PhD as appropriate and select October 2018 for study option (this can be updated at a later date if required)
(b) in ‘Research Project Information’
You will be provided with a free text box for details of your research project. Enter Title and Reference number of the project for which you are applying and also enter the supervisor’s name.
This information will greatly assist us in tracking your application. Please note that once you have submitted your application, it will not be considered until you have uploaded your CV and transcripts.