has primary place
type: ObjectProperty
type: FunctionalProperty
type: Property

homepage
type: AnnotationProperty
type: InverseFunctionalProperty
type: Property
type: ObjectProperty

email
type: ObjectProperty

University of Oxford
legal-foi: foi
events: events-list
press-facts: facts-and-figures
research: research
account: oxford
space-accessibility: access
about-strategy: strategic-plan
about-executive: governance
about-parents: P&C guide 2013.pdf
conference-facilities: www.conference-oxford.com
legal-website: legal
contact-staff: staff
uk-ico-publication-scheme: publication
undergraduate: undergraduate
display in maps department list: false
postgraduate: graduate
undergraduate-courses: courses-listing
address: Address
  extended address: University of Oxford
  street address: Wellington Square
  locality: Oxford
  country name: United Kingdom
  postal code: OX1 2JD
events-graduation: graduation
legal-data-protection: dataprotection
opendays: open-events-and-visiting
support-depts: services az
press: news-and-events
legal-equality: eop
courses: admissions
account: UniofOxford
jobs: jobs
legal-regulations: statutes
about-leader: vice-chancellor
contact: contact-us
open-data: data.ox.ac.uk
ict-support: help.it.ox.ac.uk
sort label: Oxford, University of
business: innovation-and-partnership
type: university
postgraduate-taught-courses: taught-courses
undergraduate-courses-entry-requirements: selection-criteria
account: university-of-oxford
postgraduate-research-courses: research-courses
news: news-and-events
legal-ict: 196-052.shtml
notation: 00000000
about: organisation
depts: departments-a z
about-sites: how-get-oxford
account: the.university.of.oxford

Computer Science Library
Old OLIS code: Computing Lab
notation: COMDL
display in maps department list: false
address: Address
  street address: Parks Road
  country name: United Kingdom
  extended address: Room 240, Wolfson Building
  locality: Oxford
  postal code: OX1 3QD
notation: Computing Lab
subOrganization of: Department of Computer Science
occupies: Wolfson Building
notation: COM
has primary place: Wolfson Building
Old OLIS code: COM
Is Part Of: Department of Computer Science
library description page: http://www.bodleian.ox.ac.uk/subjects-and-libraries/libraries
OLIS code: COMDL
notation: 32320013
primary Site: Wolfson Building
has site: Wolfson Building
type: library
has library data id: 50

Agent
type: Class

Voice
type: Class

OpenStreetMap feature identifier
type: Property
type: InverseFunctionalProperty
type: AnnotationProperty

169235 Job description and selection criteria
type: Document
value: _________________________________________________________________________ University of Oxford Department of Computer Science Job description and selection criteria Job title Research Assistant on Deep Learning for Image Artifact Removal Division Mathematical, Physical and Life Sciences (MPLS) Department Computer Science Location Wolfson Building, Parks Road, Oxford. Grade and salary Grade 6: £32,332 - £38,205 per annum Hours Full time (part time can be considered) Contract type Fixed-term for up to 1 year Reporting to Professor Ana Namburete Vacancy Reference 169235 Research topic Physics-informed ultrasound image artifact removal Principal Investigator / Professor Ana Namburete supervisor Project team Project web site Funding partner Recent publications Oxford Machine Learning in Neuroimaging Laboratory (OMNI) https://omni.cs.ox.ac.uk/ ; https://pakheiyeung.github.io/ImplicitVol_wp/ The funds supporting this research project are provided by the Bill and Melinda Gates Foundation Yeung et al. ImplicitVol: Sensorless 3D ultrasound reconstruction with deep implicit representation. Medical Image Analysis 2023 (accepted) [arXiv] [project page] Overview of the role Live imaging is an essential diagnostic tool in modern medicine. Two-dimensional (2D) ultrasound is a fast, safe, and affordable tool, making it ideal to monitor the baby in the womb, and to detect any brain abnormalities during pregnancy. However, ultrasound images are affected by artifacts such as acoustic shadows, speckle, and scattering which hamper the visibility of internal structures. Removal of these image artifacts could bolster the utility of ultrasound as a screening tool in a range of medical applications. An exciting opportunity has become available for a research assistant to investigate novel deep neural networks that significantly minimise the impact of image artifacts on routinely acquired ultrasound images. Our clinical partner for this project is the Leiden University Medical Centre (LUMC, L…
Format: application/pdf

Description of Research Assistant on Deep Learning for Image Artifact Removal
has format: RDF/XML description of Research Assistant on Deep Learning for Image Artifact Removal
has format: HTML description of Research Assistant on Deep Learning for Image Artifact Removal
primary topic: Research Assistant on Deep Learning for Image Artifact Removal
type: Document
has format: NTriples description of Research Assistant on Deep Learning for Image Artifact Removal
has format: Turtle description of Research Assistant on Deep Learning for Image Artifact Removal
has format: Notation3 description of Research Assistant on Deep Learning for Image Artifact Removal

subOrganization of
label: sous-Organization de @fr
type: Property
label: sotto-Organization di @it
type: ObjectProperty
label: es suborganización de @es

HTML description of Research Assistant on Deep Learning for Image Artifact Removal
Format: application/xhtml+xml
Format: text/html

primary Site
label: tiene sede principal en @es
label: sede principale @it
label: site principal @fr
type: ObjectProperty
type: Property

has max currency value (1..1)
type: DatatypeProperty

Grade 6: £32,332 - £38,205 per annum
valid through (0..1): 2023-11-13T12:00:00+00:00
salary grade: 6
has max currency value (1..1): 38205
has min currency value (1..1): 32332
type: Unit price specification
has currency (1..1): GBP

Subject
type: Property
type: ObjectProperty

Wolfson Building
latitude: 51.75997
Is Part Of: http://oxpoints.oucs.ox.ac.uk/id/40006000
within: http://oxpoints.oucs.ox.ac.uk/id/40006000
OpenStreetMap feature identifier: way/197021482
notation: 40006001
address: Address
  locality: Oxford
  country name: United Kingdom
  postal code: OX1 3QD
  street address: Parks Road
longitude: -1.258246
type: building

has site
label: a un site @fr
type: Property
label: ha sede @it
type: ObjectProperty
label: tiene sede en @es

preferred label
type: AnnotationProperty
type: Property

library description page
type: Property
type: ObjectProperty

street address
type: DatatypeProperty

building
type: Class

has currency (1..1)
type: DatatypeProperty

OLIS code
type: AnnotationProperty
type: InverseFunctionalProperty
type: Property

extended address
type: DatatypeProperty

account
type: Property
type: ObjectProperty

Document
type: Class

telephone
type: ObjectProperty

Format
type: Property

Notation3 description of Research Assistant on Deep Learning for Image Artifact Removal
Format: text/n3

HR Coordinator
type: Agent

Research Assistant on Deep Learning for Image Artifact Removal
application opening date: 2023-11-06T09:00:00+00:00
subject: research
comment: 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.
salary: Grade 6: £32,332 - £38,205 per annum
internal applications only: false
application closing date: 2023-11-13T12:00:00+00:00
contact: HR Coordinator
based near: Wolfson Building
spatial: Computer Science - Wolfson Building, Parks Road, Oxford
type: Vacancy
further particulars: 169235 Job description and selection criteria
organization part: Computer Science Library
notation: 169235
formal organization: University of Oxford
comment: 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.

valid through (0..1)
type: DatatypeProperty

Title
type: AnnotationProperty
type: Property

occupies
type: Property
type: ObjectProperty

notation
type: DatatypeProperty
type: Property

locality
type: DatatypeProperty

OxPoints
License: http://creativecommons.org/publicdomain/zero/1.0/
type: Dataset

Turtle description of Research Assistant on Deep Learning for Image Artifact Removal
Format: text/turtle

NTriples description of Research Assistant on Deep Learning for Image Artifact Removal
Format: text/plain

image
type: ObjectProperty
type: Property

has exact match
type: SymmetricProperty
type: TransitiveProperty
type: Property
type: ObjectProperty

Title
type: DatatypeProperty
type: Property

logo
type: ObjectProperty
type: InverseFunctionalProperty
type: Property

page
type: ObjectProperty
type: Property

name
type: Property
type: DatatypeProperty

License
type: Property
type: AnnotationProperty

based near
type: ObjectProperty
type: Property

Old OLIS code
type: AnnotationProperty
type: InverseFunctionalProperty
type: Property

address
type: ObjectProperty

longitude
type: Property

latitude
type: Property

Unit price specification
type: Class

Department of Computer Science
type: Department

library
type: Class

label
type: Property

Address
type: Class

comment
type: Property

in dataset
type: ObjectProperty

Past vacancies at the University of Oxford
type: Dataset

Source
type: Property

has min currency value (1..1)
type: DatatypeProperty

depiction
type: Property
type: ObjectProperty

postal code
type: DatatypeProperty

type
type: Property

value
type: Property

university
type: Class

Is Part Of
type: Property

Fax
type: Class

RDF/XML description of Research Assistant on Deep Learning for Image Artifact Removal
Format: application/rdf+xml

country name
type: DatatypeProperty