Research Assistant on Deep Learning for Image Artifact Removal

An exciting opportunity has become available for a research assistant to
investigate novel deep neural networks that significantly minimize the impact
of image artifacts on clinical ultrasound images.





The role of the research assistant in this project will be to develop and
implement deep learning-based algorithms for physics-informed removal of image
artifacts, such as acoustic shadows, speckle, and scattering.





The successful candidate will hold a first degree in computer science or
medical engineering. You are expected to have knowledge of deep learning
applied to ultrasound imaging data, particularly for the application of
artifact removal. Proficiency in Python programming using deep learning
libraries (e.g., Pytorch) are also required.





All applicants must complete an application form and submit a CV and
supporting statement.





**The closing date for applications is 12 noon on 13 November 2023.**
Interviews are expected to be held in November.





**We are a Stonewall Silver Employer, Living Wage, holding an Athena Swan
Bronze Award, HR excellence in Research and Race Equality Charter Bronze**
**Award.**





Our staff and students come from all over the world and we proudly promote a
friendly and inclusive culture. Diversity is positively encouraged, through
diversity groups and champions, for example
http://www.cs.ox.ac.uk/aboutus/women-cs-oxford/index.html , as well as a
number of family-friendly policies, such as the right to apply for flexible
working and support for staff returning from periods of extended absence, for
example shared parental leave.





Demonstrating a commitment to provide equality of opportunity. We would
particularly welcome applications from women and black and minority ethnic
applicants who are currently under-represented within the Computer Science
Department. All applicants will be judged on merit, according to the selection
criteria.