Research Fellow in Image analysis / Machine learning / Open software University of Edinburgh United Kingdom

Location: Edinburgh
Salary: £33,199 to £39,609 p.a.
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 5th July 2019
Closes: 8th August 2019
Job Ref: 048500

 

Fixed term for 9 months

We are looking for an enthusiastic and ambitious Research Fellow to help accelerate biomedical research through open source software.

QuPath is popular open software that aims to make sophisticated bioimage analysis intuitive and user-friendly (https://qupath.github.io). You will work with the creator of QuPath to devise and implement new methods to analyse large and complex biomedical images using deep learning and other techniques, while helping to support the needs of the user community worldwide.

Images play a vital role in biomedical research, but bioimage analysis remains difficult. For example, analysing a single 40 GB whole slide image might involve detecting and classifying millions of cell nuclei within a large tissue section, quantifying biomarker expression for each cell, and interrogating their complex spatial arrangements. Such challenging images and analyses play an essential role in the area of digital pathology and are becoming increasingly common across a broad range of research studies.

QuPath is designed to give a wide variety of users – including biologists, pathologists, bioinformaticians, image analysts and machine learning experts – the tools they need to analyse whole slide and microscopy images effectively. Since its release at the end of 2016, QuPath has been downloaded more than 45,000 times and used in over 100 publications. You will have a unique opportunity to directly impact biomedical research by applying your skills and creativity to improve software already being used in many important studies across the world.

The overarching aim of this post is to address unsolved challenges in bioimage analysis through open science, with a special focus on providing the community with practical, generic algorithms that can be applied to many studies. This requires both powerful analysis techniques and user-friendly implementations, and there is scope for the successful candidate to concentrate more on algorithm or software development, depending upon their skills and interests.

This is a fixed-term position for 9 months, however QuPath is envisaged as a long-term project and further funding is actively being sought to build a core development team to ensure its ongoing sustainability. There may therefore be opportunities for extension, subject to future funding being available.

This post is available on a fixed term basis, with a working pattern of 35 hours per week for 9 months.

Informal enquiries can be made to igmmhr@igmm.ed.ac.uk

For more information and to submit an application, please use the 'apply' button.


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