Research Assistants/Associates – Biomedical Image Analysis and Machine Learning
Health and Medical,Medical Technology,Computer Science,Computer Science,Artificial Intelligence
Short info about job
Company: Imperial College London
Department: Department of Computing
Salary: £32,380 to £44,220 per annum
Hours: Full Time
Contract type: Fixed-Term/Contract
Type / Role: Academic or Research
Phone: +44-1466 1781402
Fax: +44-1568 7176513
Detail information about job Research Assistants/Associates – Biomedical Image Analysis and Machine Learning. Terms and conditions vacancy
Two Research Assistants/Associates – Biomedical Image Analysis and Machine Learning
Research Assistant salary range: £32,380 to £34,040 per annumResearch Associate salary range: £36,800 to £44,220 per annum
Fixed Term appointments up to 31 August 2019
The BioMedIA group is part of the Department of Computing which is a leading department of Computer Science among UK Universities. Imperial College has the greatest concentration of high impact research of any major UK university, according to the Research Excellence Framework (REF) 2014. Imperial was also awarded “Gold” according the last Teaching Excellence Framework (TEF) 2017.
We are seeking to appoint two Research Assistant/Associates to develop image analysis tools as well as machine learning tools for the Developing Human Connectome Project (dHCP – http://developingconnectome.org). dHCP develops and applies novel, cutting-edge magnetic resonance (MR) methods to record structural and functional cerebral connectivity during early life, creating the first mapping of the developing human macro-connectome.
The successful candidates will help improve existing tools for image reconstruction and segmentation (including parcellation and cortical surface reconstruction) as well as contribute to the development of novel tools to process and analyse neonatal and fetal brain MR images. In addition to structural MR imaging, the dHCP project also acquires diffusion and functional MRI so expertise in the analysis of diffusion/functional MRI and/or brain connectivity would be useful.
At Research Assistant level you will need to have a good (1st or 2.1) undergraduate degree in a relevant discipline with a particular interest in medical image computing, computer vision or machine learning. Preference will be given to applicants with a proven track record in medical imaging and excellent programming skills. To be appointed at Research Associate level you must have been awarded a PhD (or equivalent) in a subject relevant to medical imaging with particular expertise in medical image computing, computer vision or machine learning.
All applicants must be fluent in spoken and written English. You must have excellent communication skills and be able to organise your own work with minimal supervision and prioritise work to meet deadlines.
You will be part of the Biomedical Image Analysis Group (BioMedIA) based at the South Kensington campus in London. The mission of the group is to develop novel, computational techniques for the analysis of biomedical images. For further information about the group and related projects see: http://biomedic.doc.ic.ac.uk/.
How to apply:Our preferred method of application is online via our website at: http://www3.imperial.ac.uk/employment.
Please select “job search” then enter the job title or vacancy reference number EN2017224LE into “keywords”. Please complete and upload an application form as directed.
Applications must include the following:
- A college application form
- A full CV
- A two-page research statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant.
- Any element relating your experience / passion for software engineering (blog, open source projects, github repositories and others) will be carefully inspected.
Should you have any queries regarding the application process please contact Georgina Tennant by email to: [email protected]
Committed to equality and valuing diversity. We are also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Two Ticks Employer, and are working in partnership with GIRES to promote respect for trans people