Deep Learning for Video Segmentation - Research

Ulster University - Jordanstown


Course Name Deep Learning for Video Segmentation - Research
Course Provider Ulster University - Jordanstown
Course Code 110489 (Assigned by Qualifax. Not an official code)
Course Type Postgraduate
Award NameNFQ ClassificationAwarding BodyNFQ Level
Degree - Doctoral at UK Level 8  Comparing Qualifications in the UK and Ireland Ulster University None
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Attendance Options Full time, Part time, Daytime
Location (Districts) Jordanstown
Qualification Letters PhD
Enrolment and Start Dates Comment Key dates
Submission deadline: Sunday 11 April 2021.

Interview Date: 1 May 2021.

Preferred student start date: Mid-September 2021.
Application Date Application process for prospective research students:
The University admits researchers on the basis of a policy of equality of opportunity and welcomes applications from all sections within the community.

To apply please see "Application Weblink" below.
Application Weblink Web Page - Click Here
Link to Course Fee Web Page - Click Here
Financial Support

Expand+The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

Department for the Economy (DFE)
The scholarship will cover tuition fees at the Home rate a...

Entry Requirements

Expand+Essential criteria
To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.

Desirable Criter...

Comment Key information
Subject: Computer Science and Informatics
Funded PhD Opportunity
Course Content

The School of Computing is seeking to recruit a PhD researcher to work on Deep Learning for Video Segmentation to support a three-year EPSRC funded research project, which will develop new technologies enabling users to search efficiently an...

Further Enquiries Contact supervisor
Professor Bryan Scotney
Telephone +44 28 7012 4648
Course Web Page Web Page - Click Here