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Doctor of Philosophy in Applied Mathematics (By Research)

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Universiti Sains Malaysia (USM)(Penang Campus )

Doctor of Philosophy in Applied Mathematics (By Research)

university icon
Universiti Sains Malaysia (USM)(Penang Campus )

Doctor of Philosophy in Applied Mathematics (By Research)

Qualification
Doctoral Degree (PhD)
Duration
2 years
Intake
OctOct
English Requirement
Not Required
Offer Letter
Fees Applies
Class Type
Physical
Course Fee for International Students
Yearly Tuition fees
Year Fee
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Universiti Sains Malaysia (USM) ?

The Doctor of Philosophy in Applied Mathematics (by Research) at Universiti Sains Malaysia (USM) is a research-focused postgraduate programme offered by the School of Mathematical Sciences. It is designed for students who wish to develop advanced expertise in mathematical theory and its applications to real-world problems.

This PhD programme requires students to conduct independent and original research under the supervision of academic staff, culminating in a thesis that contributes new knowledge to the field.

The programme is suitable for both local and international candidates and may be pursued full-time or part-time. Typical completion time ranges from a minimum of 4 semesters (full-time) to up to 10 semesters, with a similar extended period available for part-time study.

Students develop skills in independent research, problem-solving using advanced mathematical tools, critical thinking, and academic writing. Graduates are well-equipped for careers in academia, research institutions, government, and industry sectors that require high-level quantitative and analytical expertise.

Entry Requirements

 A Master’s degree in related area with CGPA 3.00/4

For other qualifications and certificates (e.g., Other qualifications equivalent to a Master’s degree , etc..) please contact our educational consultants or submit your application for Admission assessment.

Research areas

  • Numerical Analysis
  • Parallel Numerical Algorithms
  • Cryptography
  • Functional Differential Equations
  • Convergence and Learning Algorithms of Neural Network
  • Differential Equations
  • Neural Networks
  • Numerical Linear Algebra
  • Optimazations
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