# Master of Mathematical Sciences

## Overview

In our increasingly technological world the study of mathematics is vital to future developments and discoveries. A foundation in this area will enable you to apply logic and quantitative reasoning to a vast array of situations, changing the way you think about your surroundings and how things work.

The Master of Mathematical Sciences (MMathSci) degree has been designed to provide thorough internationally competitive training in mathematics and to provide a bridge between undergraduate studies and future research in mathematical sciences.

Undergraduate students from the University of Sydney wishing to undertake the Master of Mathematical Sciences are expected to have completed a major in Mathematics, Statistics, Data Science, or Financial Mathematics and Statistics.

The degree will provide thorough training in the mathematical sciences for students who wish to transition from undergraduate studies to research in the mathematical sciences, and will provide a solid foundation for PhD studies.

See also the information concerning the Master of Mathematical Sciences in the University's courses database.

## About the Degree

The length of the MMathSci is two years full-time, or four years part-time (for domestic students). It consists of 96 credits, 72 for coursework and 24 for a written thesis project.

Of the 72 coursework credits, up to 24 can come from 3000 level units, up to 48 can come from 4000 level units, and at least 12 must come from 5000 level units. In addition, one can apply to obtain up to 24 credits of "reduced volume in learning", which can be awarded for already completed undergraduate coursework equivalent to courses which comprise the MMathSci.

The research project will be undertaken under the direction of a supervisor among the faculty of the School of Mathematics and Statistics. Accepted MMathSci students are encouraged to contact faculty with aligned research interests to seek out projects.

Credit for the research project is allocated by enrolling in the project units A-D, which are tagged MSCI5101-5104. These are "shell units", which serve to allocate research time during the degree. Students have flexibility when to take these units. One common option is to take only coursework during the first year of the degree, and during the second year of the degree take two project units per semester. This allocates 50% research time during the second year of the degree. Another option is to take one project unit every semester, allocating 25% research time for the duration of the degree. Please consult with your supervisor about your schedule.

At the end of the degree, students submit a written thesis for evaluation.

## Frequently Asked Questions

- I am trying to enrol in a 3000 level unit, and I am being prohibited due to prerequisite requirements. What do I do?

Don't worry - as an MMathSci student you can enrol in any 3000 level unit regardless of prerequisite requirement. Unfortunately, one has to apply for an Enrolment Exemption Request, but these are very quickly approved.

## Units of Study

The 4000 level units on offer this year are listed on the Honours Website.

The are two 5000 level units on offer in Semester 2, 2021:

- STAT5611: for information please contact Michael Stewart or Neville Weber.
- MATH5341: for information please contact Gus Lehrer or Laurentiu Paunescu.

In general, the following units of study may be counted as part of the requirements for the degree:

- Advanced Dynamical Systems (MATH4414)
- Advanced Inference (STAT5610)
- Advanced Methods in Applied Mathematics (MATH4412)
- Advanced Statistical Modelling (STAT4027)
- Algebraic Topology (MATH4311)
- Applied Computational Mathematics (MATH4411)
- Applied Linear Models (Advanced) (STAT3922)
- Applied Mathematical Modelling (MATH4413)
- Applied Statistics for Complex Data (DATA5710)
- Arbitrage Pricing in Continuous Time (MATH4511)
- Bayesian Computational Statistics (DATA5711)
- Commutative Algebra (MATH4312)
- Complex Analysis (MATH4079)
- Computational Mathematics (MATH4076)
- Convex Analysis and Optimal Control (MATH4071)
- Data Science Capstone (DATA3888)
- Deterministic and Stochastic Systems (MATH5420)
- Differential Geometry (MATH4068)
- Dynamical Systems and Applications (MATH4063)
- Financial Derivatives (Advanced) (MATH3975)
- Fluid Dynamics (MATH4074)
- Functional Analysis (MATH4313)
- Lagrangian and Hamiltonian Dynamics (MATH4077)
- Linear and Mixed Models (STAT4022)
- Mathematical Models for Natural Phenomena (MATH5430)
- Measure Theory and Fourier Analysis (MATH4069)
- Metric Spaces (MATH4061)
- Networks and High-dimensional Inference (DATA5441)
- Optimal Control and Game Theory (MATH5550)
- PDEs and Applications (MATH4078)
- Probability and Martingale Theory (STAT4528)
- Probability and Mathematical Statistics (STAT4028)
- Projects in Financial Mathematics (FMAT3888)
- Projects in Mathematics (MATH3888)
- Representation Theory (MATH4314)
- Rings, Fields and Galois Theory (MATH4062)
- Special Topics in Applied Mathematics (MATH5410)
- Statistical Consulting (STAT4026)
- Statistical Inference (Advanced) (STAT3923)
- Statistical Machine Learning (STAT3888)
- Statistical Methodology (STAT5611)
- Stochastic Analysis (MATH4512)
- Stochastic Processes (Advanced) (STAT3921)
- Stochastic Processes and Applications (STAT4021)
- Stochastics and Finance (MATH5551)
- Theory and Methods of Statistical Inference (STAT4023)
- Time Series (STAT4025)
- Topics in Algebra (MATH5310)
- Topics in Analysis (MATH5320)
- Topics in Financial Mathematics (MATH4513)
- Topics in Geometry (MATH5330)
- Topics in Topology (MATH5340)
- Variational Methods (MATH4315)