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How To Apply For EPSRC DTP PhD Studentships in Building Interpretable Generative Models of Images at the University of Sussex, UK 2022-23

This is to bring to your notice that the application window for the EPSRC DTP PhD Studentships in Building Interpretable Generative Models of Images at the University of Sussex, UK 2022-23, iis now open for interested and qualified applicants.

EPSRC DTP PhD Studentships

Important Points 

Listed below are the summarized points you need to note about the Scholarship Programme:

  • Funding is partial 
  • They take Building interpretable generative models of images at the University of Sussex 
  • International students are eligible
  • All PhD students are eligible

Brief Description

The University of Sussex is thrilled to offer bright candidates in the UK the EPSRC DTP PhD Studentships in Interpretable Generative Models of Images. For the school year 2022-2023, the institution is accepting applications.

This project intends to provide a machine learning framework for learning human interpretable picture representations, in which variations are broken into different semantically significant components such as form, identity, posture, texture, lighting, and so on.

Application Deadline

Application deadline is June 10, 2022.

Eligible Courses

The EPSRC DTP PhD Studentships in Building Interpretable Generative Models of Images at the University of Sussex, UK 2022-23 is a scheme that looks to reward high-achieving internationals, and it is only available for the course below:

  • Building interpretable generative models of images 

Eligible Countries 

Students from the following nationalities are eligible:

  • All countries 

Scholarship Award Benefit

All of the following will be provided by the university:

  • For 3.5 years, the institution will pay a £16,062 Standard UKRI stipend, a £1,650 research training grant, and full tuition costs up to the international rate.

Degree Type 

The EPSRC DTP PhD Studentships in Building Interpretable Generative Models of Images at the University of Sussex, UK 2022-23, is primarily for PhD programs.

Number of Awards

Not specified 

Eligibility Criteria

All applicants must meet the following criteria to be considered for the EPSRC DTP PhD Studentships in Building Interpretable Generative Models of Images at the University of Sussex, UK 2022-23:

  • Candidates must have a 2:1 degree or equivalent in a related discipline to be considered.
  • Must be from the United Kingdom, the European Union, or another country.
EPSRC DTP PhD Studentships

Application Procedure

To apply, all arranged and organized steps have been highlighted below for the EPSRC DTP PhD Studentships in Building Interpretable Generative Models of Images at the University of Sussex, UK 2022-23:

  • For this financial option, students must apply to the university’s selected PhD program using an online application. Please make it explicit on your application form that you are applying for the EPSRC DTP 2022, which will be supervised by Dr. Ivor Simpson (I.Simpson@sussex.ac.uk).
  • Documents to Support: When applying, applicants must present the following documents:
    • Research proposal/statement of research
    • Academic interests summarized (this is optional depending on the subject area you are applying for)
    • Certificates of completion and transcripts Certified translations must be given if the originals are not in English. CV
    • Two academic references, one from your most recent college or institution. Alternatively, you may send your references’ contact information to us.
  • Admission Requirements: Students must have to check the specific entry requirements listed with each PhD degree at the university.
  • Language Requirement: If your first language is not English, you will need to demonstrate that you meet the University’s English language requirements for the degree you have applied for.

Please click the EPSRC DTP PhD Studentships in Building Interpretable Generative Models of Images at the University of Sussex, UK 2022-23, to begin your application.

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