| Program start date | Application deadline |
| 2024-02-26 | - |
| 2024-07-15 | - |
| 2025-03-03 | - |
| 2025-07-21 | - |
Program Overview
The Master of Mathematical Modelling (MMathModel) at the University of Auckland is a postgraduate program that equips students with advanced mathematical and computational techniques for real-world problem-solving. This cross-faculty collaboration between the Department of Mathematics and the Department of Engineering Science emphasizes a multidisciplinary approach, preparing graduates for careers in data analysis, research, and other quantitative fields. The program offers both 120- and 180-point pathways, providing flexibility for students with varying backgrounds and career goals.
Program Outline
Master of Mathematical Modelling (MMathModel) - The University of Auckland
Degree Overview:
Overview:
The Master of Mathematical Modelling (MMathModel) is a postgraduate program designed to equip students with advanced mathematical and computational techniques for real-world problem-solving. This program focuses on real-world applications such as modelling transport networks, epidemics, and climate change.
Objectives:
- Equip graduates with advanced mathematical and computational techniques for real-world problem-solving.
- Build expertise in advanced computational tools, fundamental theoretical principles, and underlying assumptions.
- Prepare students for careers in data analysis, research, and other quantitative fields.
Program Description:
The MMathModel is a cross-faculty collaboration between the Department of Mathematics and the Department of Engineering Science. It is offered with both 120- and 180-point pathways, providing flexibility for students with varying backgrounds and career goals. The program emphasizes a multidisciplinary approach, equipping graduates with a strong foundation in both mathematics and real-world applications.
Outline:
Core Courses:
The program comprises four core courses that lay the foundation for mathematical modelling principles and applications:
- MATHS 765: Mathematical Modelling
- MATHS 787: Special Topic: Inverse Problems and Stochastic Differential Equations
- ENGSCI 711: Advanced Mathematical Modelling
Elective Courses:
Students can choose from a broad range of elective courses focusing on specific areas of interest, including:
- Engineering Science: Computational Algorithms for Signal Processing, Advanced Mechanics in Research and Technology, Advanced Modelling and Simulation in Computational Mechanics, Decision Making in Engineering, Algorithms for Optimisation, Integer and Multi-objective Optimisation, Advanced Simulation and Stochastic Optimisation, Advanced Optimisation in Operations Research, Advanced Operations Research and Analytics.
- Mathematics: Dynamical Systems, Nonlinear Partial Differential Equations, Advanced Partial Differential Equations, Inverse Problems, Stochastic Differential and Difference Equations, Advanced Numerical Analysis.
- Physics: Advanced Statistical Mechanics and Condensed Matter, Waves and Potentials, Photonics, The Dynamic Universe, Quantum Optics and Quantum Information, Advanced Imaging Technologies.
- Other: Musculoskeletal and Orthopaedic Biomechanics, Econometrics 1, Econometrics 2, Research Methods – Modelling.
Research Project:
All students undertake a 45-point research project, allowing them to apply theoretical knowledge to real-world problems and develop independent research skills.
Assessment:
The program utilizes diverse assessment methods to evaluate student learning outcomes, including:
- Assignments: Problem sets, essays, and case studies to assess comprehension and application of theoretical concepts.
- Examinations: Written exams to assess understanding of core knowledge and problem-solving skills.
- Presentations: Oral presentations to develop communication and critical thinking skills.
- Research Project: A comprehensive project, assessed through written reports and presentations, to demonstrate independent research capabilities.
Teaching:
The MMathModel program adopts a multifaceted approach to teaching, incorporating lectures, tutorials, workshops, and project supervision. This ensures a strong foundation in theoretical concepts, practical application, and hands-on experience.
Faculty:
The program draws on expertise from leading researchers and academic staff in mathematics, engineering science, and related fields. Their combined knowledge and experience contribute to a high-quality and insightful learning experience.
Teaching Methods:
The program employs interactive teaching methods, including:
- Problem-based learning: Students actively engage in solving real-world problems using mathematical and computational tools.
- Collaborative learning: Group projects and discussions encourage team-based learning and peer-to-peer interactions.
- Case studies: Real-world examples illustrate theoretical concepts and their practical applications.
Careers:
Career Opportunities:
The MMathModel equips graduates with a wide range of transferable skills applicable to diverse career paths. They are well-prepared for roles in data analysis, research, modelling, consulting, and other quantitative fields.
Potential Employers:
- Government agencies: Ministry of Health, Ministry for the Environment, Statistics New Zealand
- Research institutions: The Alan Turing Institute, SINTEF, University of Oxford
- Private companies: Google, Amazon, McKinsey & Company
Specific Career Examples:
- Data Scientist
- Statistician
- Operations Research Analyst
- Mathematical Modeller
- Research Scientist
- Consultant
- Quantitative Analyst
Other:
Program Duration:
The program can be completed in 1 year (for 120-point pathway) or 1.5 years (for 180-point pathway).
Locations:
City campus
Entry Requirements:
- Bachelor's degree in relevant field (analytics, applied mathematics, artificial intelligence, computer science, data science, engineering, operations research, physics, software engineering, structural engineering, electrical engineering, statistics, technology) with a GPA of 4.0 or higher.
- Relevant coursework in mathematics, computer programming, and partial differential equations.
Language Requirements:
With a focus on real-world applications and advanced tools, this program equips graduates for impactful careers in data-driven fields.
Entry Requirements:
There are distinct entry requirements for two different cohorts of students: EU home students and international overseas students outside the EU.
EU Home Students:
Bachelor's Degree:
An undergraduate degree in a relevant subject. Relevant subjects include analytics, applied mathematics, artificial intelligence, computer science, data science, engineering, operations research, physics, software engineering, structural engineering, electrical engineering, statistics, or technology.
Grade Point Average (GPA):
You must have achieved a GPA of 4.0 in either:
- Your 120-point Bachelor's degree
- A Postgraduate Diploma coupled with a Bachelor's degree (both in a relevant subject)
Specific Course Completion:
You must have finished at least 15 points from 2 pre-requisite courses: MATHS 162 and COMPSCI 130.
OR
You must have finished at least 15 points from 4 pre-requisite courses: ENGSCI 311, ENGSCI 313, ENGSCI 314, and MATHS 361
International Overseas Students (Outside EU):
English Language Proficiency:
Applicants must fulfill one of the following requirements:
- An IELTS Academic score of 6.5 with no band score lower than 6.0.
- An appropriate equivalent score in an approved English language test.
Bachelor's Degree:
- Applicants must have completed either:
- One year of postgraduate study with a GPA of 4.0. This post-graduate study must come after obtaining an undergraduate degree in a relevant field.
- An undergraduate degree from a recognized institution in a relevant field with a GPA of 4.0 and have three years of relevant professional experience.
- Relevant subjects include analytics, applied mathematics, artificial intelligence, computer science, data science, engineering, operations research, physics, software engineering, structural engineering, electrical engineering, statistics, or technology.
Specific Course Completion:
Applicants must have achieved at least 15 points from these two pre-requisite courses: MATHS 162 and COMPSCI 130. For international overseas students (outside the EU), this program requires applicants to demonstrate English language proficiency by achieving:
- IELTS Academic: Score of 6.5 with no band score below 6.0.
- Alternative Equivalent: Score in an approved English language test that is deemed equivalent to the 6.5 in IELTS Academic. This ensures all students, even those from non-English speaking backgrounds, have the language ability to engage effectively in classroom activities like lectures, discussions, and coursework.
