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PhD PATTERN RECOGNITION/CLASSIFIERS

Pattern recognition is a very active field of research intimately bound to machine learning and data mining. Also known as classification or statistical classification, pattern recognition aims at building a classifier that can determine the class of an input pattern. An input could be the ZIP code on an envelope, a satellite image, microarray gene expression data, a chemical signature of an oil-field probe, a financial record of a company and many more. The classifier may take a form of a function, an algorithm, a set of rules, etc. Pattern recognition is about training such classifiers to do tasks that could be tedious, dangerous, infeasible, impractical, expensive or simply difficult for humans. Pattern recognition faces many challenges in the modern era of massive data collection (e.g. in retail, communication and Internet) and high demand for precision and speed (e.g. in security monitoring and target tracking). New methodologies are needed to answer these application-born challenges.

Intakes

Application Processing Time in Days: 20

Minimum English Language Requirements

English Level Description	IELTS (1.0 -9.0)	TOEFL IBT (0-120)	TOEFL CBT (0-300)	PTE (10-90)
Expert	9	120	297-300	86-90
Very Good	8.5	115-119	280-293	83-86
Very Good	8	110-114	270-280	79-83
Good	7.5	102-109	253-267	73-79
Good	7	94-101	240-253	65-73
Competent	6.5	79-93	213-233	58-65
Competent	6	60-78	170-210	50-58
Modest	5.5	46-59	133-210	43-50
Modest	5	35-45	107-133	36-43
Limited	4	32-34	97-103	30-36
Extremely Limited	< 4	< 31	< 93	< 30

Job Opportunity Potential

Many courses help strengthen career prospects through;

Work placements: students are provided with a variety of options for work experience – either within the degree, through University internships or by volunteering.
Industry partnerships: Some degrees are run in partnership with the industry such as Teacher Training, Nursing and Social Work.
Professional accreditations: to help develop students’ careers, many of the degrees are accredited by professional bodies of global repute, such as IBMS, ACCA, CIMA, CIM, BCS, BPS, IET, ICF, SRA, and NMC.

PSW Opportunity

2 Years PSW is applicable after completing a minimum duration of 9 months course (like- Undergraduate, Postgraduate Level)
3 Years PSW is applicable after completing PhD level courses.

Admission Requirement / Eligibility Criteria

Research Programmes (MPhil/PhD)
For PhD: Masters degree in a relevant subject. Normally, a Distinction in your Masters degree is a requirement.

For MPhil: First or upper-second class degree in a relevant subject, such as Economics, Finance, Accounting, Business or Management.

If your native language is not English, you must provide satisfactory evidence that you have an adequate knowledge and understanding of written and spoken English:

IELTS: 7.0 (with no individual score lower than 6.5)
Pearson PTE: 67 (with no individual score lower than 62)
Cambridge English Test – Advanced/Proficiency: 185 (with no individual score lower than 176)

IELTS (SELT or Non-SELT) or IELTS Indicator (tests taken from 1st July onwards)
Bangor Business School - 7.0 (6.5)
Biological Sciences - 6.0 (5.5)
Computer Science - 6.0 (5.5)
Creative Studies & Media - 7.0 (6.5)
MRes - 6.5 (6.0)
Education - 6.5 (6.0)
Electronic Engineering - 6.0 (5.5) - (Writing 6.5)
English Literature - 6.5 (6.0)
Environment, Natural Resources & Geography - 6.5 (6.0)
Healthcare Sciences - 7.0 (7.0)
History, Welsh History & Archaeology - 6.0 (5.5)
Law - 7.0 (6.5)
Linguistics & English Language - 6.0 (5.5)
Medical Sciences - 6.0 (5.5)
Modern Languages - 6.5 (6.0)
Music - 6.5 (6.0)
Ocean Sciences - 6.5 (6.0)
Philosophy and Religion - 7.0 (6.5)
Psychology - 6.5 (6.0)
MRes, Master by Research - 6.5 (6.0)
IMSCAR - 7.0 (6.5)
Social Sciences - 6.5 (6.0)
Sport, Health & Exercise Science - 6.5 (6.0)
Welsh - 6.0 (5.5)

Bangor University

Bangor , Wales ,United Kingdom