Postdoctoral Research Assistant in Deep Learning for Fetal Ultrasound Image Analysis
Grade 7: £32,817 - £40,322 p.a.
Jan 06, 2021 12:00PM
We are seeking a full-time Postdoctoral Research Assistant to work on a project developing algorithms for fetal gestational age estimation using ultrasound image analysis. The post is funded by the Gates Foundation and uses the INTERGROWTH-21st and INTERBIO-21st datasets. The post is available now and fixed term for up to 12 months.
The main responsibilities of this particular Postdoctoral Research Assistant (PDRA) position are the development and improvement of novel methods for gestational age estimation via ultrasound-based image analysis. You will develop the latter in collaboration with a clinical research fellow. You will also manage own academic research and administrative activities, which involve small scale project management, to co-ordinate multiple aspects of work to meet deadlines.
You should possess a doctorate, or near completion of a doctorate in Biomedical Ultrasound Image Analysis and have expertise with deep learning tool kits and understanding of key mathematical tools such as linear algebra and real analysis to the end of understanding advanced machine learning and computer vision/biomedical image analysis algorithms. You will also be creative, have experience of validating method with clinical researchers, and enjoy the challenges and rewards of contributing to research that is trying to have a positive impact on advancing healthcare.
Informal enquiries may be addressed to the Professor Alison Noble OBE FRS FREng (firstname.lastname@example.org).
Further information can be found at http://www.eng.ox.ac.uk/about-us/jobs
Only applications received before midday on 6 January 2021 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests, CV and the details of two referees as part of your online application.
The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.
Prof Alison Noble
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