Tools for live-cell imaging in the millisecond regime using electrically tunable lenses
- Supervisor: Dr Viji Draviam
- Deadline: 30th June 2018
- Funding: RCUK - BBSRC LIDo DTP (see BBSRC LIDo DTP website for eligibility criteria)
A BBSRC LIDo DTP industrial CASE studentship is available to start in October 2018 in the School of Biological and Chemical Sciences at Queen Mary University of London, and in collaboration with Image Solutions UK Ltd.
We are seeking a PhD student for an interdisciplinary research project to develop novel technologies for high-speed 3-dimensional imaging of dividing human cells.
Building on recent success in high-speed imaging using the Electrically Tunable Lens, the student will develop cutting-edge microscopy tools for long-term imaging of light-sensitive live-cells. For this purpose, the student will use optical engineering, computational and cell biology approaches. The student will acquire skills to exploit point-spread functions, deconvolution algorithms, microscope control software tools and light-sensitive human cell cultures. A dedicated microscope platform will be provided for generating the metadata and implementing software tools.
The work will be performed at Queen Mary University of London, in close collaboration with IMSOL. The student will have two supervisors: a primary supervisor from academia (QMUL) with nearly twenty years of experience in Cell biology and a secondary supervisor from industry (IMSOL) with extensive experience in developing bespoke imaging solutions for live-cell microscopy. In addition, the student will gain an industrial placement opportunity for a 4-6months period at IMSOL.
The student should have a fundamental understanding of Optics (preferably from a Physics background) and should have some mathematical background (either as coursework or practical thesis work). Being able to write software codes at C++ level is essential. An interest in cell biology techniques is crucial. Training will be provided for learning cell culture techniques and to generate metadata to enable the deconvolution of high-resolution image datasets.
Funding, Elgibility and Applying
Information on criteria for entry, funding eligibility and the application process can be found on the BBSRC LIDo DTP website.
Interested applicants are encouraged to contact Dr. Viji M. Draviam via email with a full CV and a short statement on their research interests (email@example.com) in advance of the deadline.