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Postdoctoral Research Associate in Multi Modal Deep Learning for Biomedical Image Analysis (2 Posts)

Salary

Grade 7: £30,817 - £40,322 p.a.

Closing date

Jun 07, 2021 12:00PM

Description

We are seeking two full-time Postdoctoral Research Associates to work on the European Research Council (ERC) Advanced Grant entitled ‘PULSE: Perception Ultrasound by Learning Sonographic Experience’. You will join an existing inter-disciplinary team of engineers and clinicians working on the research and development of next generation ultrasound systems that will be evaluated in the context of clinical obstetrics. The posts are available now and fixed-term until 31 October 2022 (grant end).  The position will be based at the Institute of Biomedical Engineering, Old Road Campus Research Building, Headington, Oxford.

 

The ambitious objective of this project is to explore how the integration of perceptual cues derived from observing sonographers in the real-world can be utilized to make ultrasound imaging and image interpretation easier for the non-specialist. We have gathered a novel dataset of full-length ultrasound video, gaze-tracking and probe motion data to understand challenges in ultrasound scanning and to build deep learning multi modal models to support sonographer’s perform tasks. The main responsibilities of the postholders will be to explore this unique dataset by developing novel multi modal methods for ultrasound-based image guidance, and real-time demonstrators to illustrate proof-of-principle potential real-world applications. 

 

You should possess a doctorate, or near completion of a doctorate, in Biomedical Image Analysis or Computer Vision and have a background in designing deep learning algorithms.  You will be creative and enjoy the challenges and rewards of contributing to research that is trying to have a positive impact on advancing healthcare.  Demonstrated ability to work well in a team and excellent communication skills are also essential.

 

Please note that this post cannot be offered as a remote-working position, as the work requires you to access clinical data and use equipment onsite.

 

Informal enquiries may be addressed to the Professor Alison Noble OBE FRS FREng (alison.noble@eng.ox.ac.uk).

 

Further information can be found at http://www.eng.ox.ac.uk/about-us/jobs 

 

Only applications received before midday on Monday, 7 June 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.


Contact name

Professor Alison Noble

Contact email

alison.noble@eng.ox.ac.uk

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