University
University of AucklandMaster of Mathematical Modelling MMathModel
This course is available
On-Campus, Online
Level of Study
Master's Degree
Summary
At present, mathematical modelling is enjoying a high degree of public awareness, with real-world applications such as COVID-19 and climate modelling frequently appearing in the news.
The Master of Mathematical Modelling will expose students to a broad range of realistic modelling techniques and provide them with expertise in advanced computational tools. Students will also gain fundamental knowledge of the underlying theoretical principles and assumptions.
This programme is available with either a 120- or 180-point pathway. It comprises core Engineering Science and Mathematics courses and a broad range of electives.
Students will also complete a research project worth 45 points.
Find out what our campus locations and facilities have to offer in these videos.
Entry criteria
Minimum requirements listed here are the likely grades required and do not guarantee entry. We assess each application individually and applicants may require a higher grade to be offered a place.
- Study option
Taught 120 points
Grade required
GPA Grade Point Average 4.0
- Study option
Taught 180 points
Grade required
GPA Grade Point Average 4.0
You must have completed either:
- a Bachelors degree and Postgraduate Diploma, each in a relevant subject and with a Grade Point Average of 4.0 or higher in 60 points above Stage III
- a Bachelors (Honours) degree with a GPA of 4.0 or higher in 60 points above Stage III
- a Bachelors (Honours) degree and passed 60 points with a GPA of 4.0 or higher in a relevant postgraduate diploma or postgraduate certificate provided that the certificate or diploma has not been awarded
You must also have completed 15 points from COMPSCI 130, ENGGEN 131, MATHS 162, and 15 points from ENGSCI 311, 313, 314, MATHS 361, or the equivalent as approved by the Programme Director.
Relevant subjects may include analytics, applied mathematics, artificial intelligence, computer science, data science, engineering, operations research, physics, software engineering, structural engineering, electrical engineering, statistics, or technology.
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