Pattern Recognition/Classifiers PhD

UK

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What will I learn?

About This Course

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.

Which department am I in?

School of Computer Science and Engineering

Study options

Full Time (3 years)

Tuition fees
£20,000.00 (US$ 25,829) per year
This is a fixed fee

*Price shown is for indicative purposes, please check with institution

Start date

Expected September 2025

Venue

Bangor University

Bangor (Wales),

LL57 2DG, WALES, Wales

Entry requirements

For international students

A good honours degree or equivalent is required. Applicants need to have an overall IELTS: 6.0 (with no element below 5.5). TOEFL 75 Overall.

*There may be different IELTS requirements depending on your chosen course.

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About Bangor University

Bangor’s outstanding course-specific facilities and passionate faculty help to ensure all students enjoy a tailored, enriching study programme.

  • Wide range of respected course options
  • Extensive facilities designed to fit each school
  • Impressive support network provided to all students
  • Fantastic scenic location with major cities in easy reach