PhD Artificial Intelligence (Transportation Optimization) - University Of Surrey, Guildford, England

CountryUnited Kingdom
Degree LevelPost Graduate
Type Academic Scholarships
Final Deadline 15 November, 2021
CitizenshipOpen
Intake Year2021

Overview

Scholarship Description:

PhD Artificial Intelligence (Transportation optimization) - University of Surrey, Guildford, England is open for International Students . The scholarship allows PhD level programm(s) in the field of Transportation Sciences, Artificial Intelligence taught at University of Surrey . The deadline of the scholarship is 15 Nov 2021.

Degree Level:

PhD Artificial Intelligence (Transportation optimization) - University of Surrey, Guildford, England is available to undertake PhD level programs at University of Surrey.

Available Subjects:

Following subject are available to study under this scholarship program.

  • Transportation Sciences
  • Artificial Intelligence

Scholarship Benefits:

  • Full tuition fee covered (UK, EU and international)
  • Stipend at 15,609 p.a. (2021/22) 
  • RTSG of £1,000 p.a. 
  • Personal Computer (provided by the department) 

Eligible Nationalities:

International Students

Eligibility Criteria:

A Bachelor’s degree or above in Computer Science, Electrical Engineering, Statistics, Mathematics, Physics or similar (a First Class or good Upper Second Class Honours degree, or the equivalent from an overseas university).

This studentship is for UK, EU and overseas students. Overseas (non-UK/EU) students will need to fund the international tuition fee difference themselves.

IELTS requirements: If English is not your first language, you will be required to have an IELTS Academic of 6.5 or above (or equivalent), with no sub-test score below 6.  

Application Procedure:

Please click ‘Apply’ on the Computer Science PhD page.

Please prepare to submit your CV; degree certificates and transcripts; names of 2 referees (ideally uploading 2 references at time of application also); and research proposal (including examples of previous project work). 

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