Application Deadline: 13th January 2025
LOCATION: United Kingdom
The Artificial Intelligence computing for the discovery of the governing knowledge of real-world systems is important. This PhD studentship offers a unique opportunity to delve into the world of Machine Learning and Knowledge Discovery. The successful candidate will work on this innovative project advancing the frontiers of this exciting field. This project could lead to Artificial Intelligence computing breakthroughs impacting data-intensive applications.
ELIGIBILITY:
Applicants for PhD MUST hold an undergraduate degree at 2.1 level in Computer Science, Mathematics or a closely related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).
As well as academic qualifications, Admissions decisions may be based on other factors, including (but not limited to): the standard of the research synopsis/proposal, performance at interview, intensity of competition for limited places, and relevant professional experience.
Applicants should have:
A strong background in Artificial Intelligence, machine learning and Knowledge Discovery computing.
Research passion for Artificial Intelligence, Machine Learning and Knowledge Discovery computing.
Excellent analytical and problem-solving skills.
Excellent computer solution research, development, evaluation skills.
Excellent academic writing skills.
English Language:
IELTS 6.5 Overall (with no individual component below 6.0) or Swansea University recognised equivalent. Full details of our English Language policy, including certificate time validity, can be found here.
As well as academic qualifications, Admissions decisions may be based on other factors, including (but not limited to): the standard of the research synopsis/proposal, performance at interview, intensity of competition for limited places, and relevant professional experience.
BENEFIT:
This scholarship covers the full cost of tuition fees and an annual stipend at £19,237.
Additional research expenses of up to £1,000 will also be available.
