ENGINEERING SCIENCE

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Postdoctoral Research Assistant in Multi Modal Deep Learning for Biomedical Image Analysis

Salary

Grade 7: £32,817 - £40,322 p.a.

Closing date

Sep 27, 2019 12:00PM

Description

We are seeking a full-time Postdoctoral Research Assistant 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.


This fixed-term post is available now with an end date of 31 October 2021 (project end date).


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 utilised 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 postholder 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. The postholder will also contribute documented software to the project, as well as collaborate with the clinical research fellow on clinical data analytics and assist in providing technical analysis input to preparation of clinical publications. You will also contribute to the curation of the PULSE dataset; this includes providing oversight of the data acquisition system and contributing to manual annotation of data.


You should possess a doctorate, or be near completion of a doctorate in biomedical image analysis or computer vision, along with experience in designing deep learning algorithms and video analysis. 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. Excellent communication skills and the ability to work well in a team are also essential.


Informal enquiries may be addressed to Professor Alison Noble OBE FRS FREng using the email address below.


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


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.


Only applications received before 12.00 noon on Friday 27 September 2019 can be considered.


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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