Job id: 074054. Salary: \xc2\xa342,405 - \xc2\xa347,178 per annum, including London Weighting Allowance.
Posted: 08 September 2023. Closing date: 22 September 2023.
Business unit: Faculty of Life Sciences & Medicine. Department: Randall Cell & Molecular Biophysics.
Contact details: Dr Susan Cox. susan.cox@kcl.ac.uk
Location: Guy\'s Campus. Category: Research.
Job description
Applications are invited for a postdoctoral research position to work on data assessment for single molecule localization microscopy in the Randall Centre for Cell and Molecular Biophysics within the Faculty of Life Sciences and Medicine at King\'s College London. This position is funded by a 3-year grant from the BBSRC Bioinformatics and Biological Resources fund.
Single molecule localization microscopy (SMLM) is a popular super-resolution fluorescence microscopy technique which has become widely used over the last fifteen years. However, producing the final images in this technique is completely dependent on image analysis of raw data, and this process is prone to generating artefacts which are not visually obvious and can lead to misleading results. Detecting these artefacts and determining image features such as spatial resolution is crucial for ensuring that accurate biological conclusions are drawn from SMLM images. In this position, you will be working with the groups of Susan Cox and Si\xc3\xa2n Culley, two leaders in the field of SMLM data assessment, Nicholas Anthony from the KCL Microscopy Innovation Centre, and a research software engineer to develop new approaches to SMLM data assessment and integrate them into packages which are of wide use to the global microscopy community.
Your work will focus on developing techniques which assess artificial sharpening, intensity linearity, and spatial resolution in SMLM images. This involve optimisation and extension of existing data assessment methods in the field, ensuring that they are robust to different types of datasets and imaging regimes, and development of novel quality control techniques. You should have a science or engineering background, with a PhD in computer science, engineering, physics, chemistry or biological sciences. Experience of a programming language is required, and experience of SMLM data analysis is an advantage.
This post will be offered on a fixed-term contract until 31st August 2026.
This is a full-time post 100% Full Time Equivalent.
Key responsibilities
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