Models are becoming an increasingly important tool in many branches of modern society due to advances in science and technology. As our understanding of these models improves, the complexity of the types of questions being asked increases. The objective of this major is to train students in techniques of model development, use and assessment.
A key requirement for future scientists, industry leaders, resource managers, and policy makers is an ability to build and evaluate models and/or interpret model outputs. Career opportunities for graduates extend into every part of society, including: research (e.g. CSIRO, Universities); public sector (e.g. Bureau of Meteorology, Murray Darling Basin Authority, state government agencies); and private sector (e.g. engineering, finance).
Students may choose to complement this major with a quantitative applications major or minor consisting of courses from areas such as: physics; earth and environmental science; global change science; climate science and policy; environmental geoscience; geophysics; quantitative finance; or mathematical finance.
Coupled with a detailed disciplinary base, this major will provide students with the necessary skills to tackle the problems facing tomorrow's society.
Learning Outcomes
- Apply mathematical concepts, including Calculus, Linear Algebra and Differential Equations to analyse specific problems and identify the appropriate mathematics to realise a solution.
- Use computer programming and statistical analysis skills to efficiently model systems.
- Recognise the connections between mathematics and other disciplines, and how mathematical ideas are embedded in other contexts.
- Represent real-world systems from science and technology in a mathematical framework.
- Employ appropriate methods to analyse, solve and evaluate the performance of mathematical models.
- Identify relevant disciplinary material and sources to pursue independent mathematical learning and deepen understanding of the behaviour of a system reasoning.
- Relate the behaviour of the output of the mathematical model to the underlying physical or conceptual model of interest.
- Extend their experiences of working both independently and collaboratively within the discipline to other contexts.
- Relate professional and disciplinary information and ideas to varied audiences in effective and appropriate ways.
- Reflect the professional standards of the discipline and of science in their own work and practice.
Other Information
By its nature, mathematical modelling is a general topic. For the non-compulsory courses in the major, we recommend that students choose courses that align with their interests and for which they satisfy the pre-requisites based on courses taken elsewhere in their degree.
What courses should you take in first year?
This major will require you to complete the following 1000-level courses:
Depending on which second-year courses you choose, you will also need to complete at least one of the following:
Students should be aware of the need to complete the pre-requisites for the 2000- and 3000- courses they wish to choose in this major.
Additional Advice:
The 2 x 1000-level MATH courses that you choose from the above are required for the 2000-level compulsory MATH; the 1000-level COMP and STAT courses are compulsory for the 2000-level COMP and STAT. All of the 3000-level courses have prerequisites. There are pathways through the major that are self-contained beyond the first year. One such route that is self-contained beyond the first year is:
MATH2305, MATH2306, MATH3501, MATH3511, STAT2005, STAT2008, STAT3015, ENGN3311.
Other pathways through the major that emphasize the application of mathematics to other disciplines (including bioinformatics, climate science, computational chemistry, computer science, and physics) are available, but students will need to plan ahead because of the need to take additional pre-requisites for courses in those disciplines.
Other MATH courses that would complement the major, that students could take using elective space in their degree (not part of the major), include:
MATH2307: Bioinformatics and Biological Modelling, MATH3133: Environmental Mathematics, MATH3512: Matrix Computations, MATH3514: Numerical Optimisation.
Academic or enrolment advice:
Students can seek further advice from the academic contact for this major (details above), or the College of Science Student Services Team (students.cos@anu.edu.au).
Relevant Degrees
Requirements
Courses marked with an asterisk (*) have 1000-level prerequisites which must be selected in the first year of study and will contribute towards satisfying the 1000-level course requirements of the Bachelor of Science or Bachelor of Science (Advanced) (Honours).
Please check individual courses for details however the courses listed below will cover most 1000-level requirements for 2000-, 3000- level courses listed in this major.
- MATH1013 or MATH1115 (or MATH1113) prerequisite for MATH1014, MATH1116 and ENGN3331 and STAT2001/STAT2005)
- MATH1014 or MATH1116 (prerequisite for MATH2305 and ENGN3331 and STAT2001/STAT2005)
- COMP1100 or COMP1110 or COMP1130 or COMP1140 or COMP1730 (prerequisites for 2000-3000 level COMP)
- STAT1003 or STAT1008 (prerequisites for 2000-level STAT)
This major requires the completion of 48 units, of which:
24 units must come from completion of the following compulsory courses:
*MATH2305 Applied Mathematics I (6 units)
*MATH2306 Applied Mathematics II (6 units)
MATH3501 Scientific and Industrial Modelling (6 units)
MATH3511 Scientific Computing (6 units)
A minimum of 6 and maximum of 12 units may come from completion of a course from the following list:
*COMP2100 Software Construction (6 units)
*STAT2001 Introductory Mathematical Statistics (6 units)
*STAT2005 Introduction to Stochastic Processes (6 units)
*STAT2008 Regression Modelling (6 units)
*STAT2013 Introductory Mathematical Statistics for Actuarial Studies (6 units)
*STAT2014 Regression Modelling for Actuarial Studies (6 units)
A minimum of 12 units must come from completion of courses from the following list:
BIOL3157 Bioinformatics and its Applications (6 units)
CHEM3208 Molecular Modelling and Computational Chemistry (6 units)
COMP3320 High Performance Scientific Computation (6 units)
COMP3600 Algorithms (6 units)
EMSC3039 Climate Dynamics (6 units)
ENGN3331 System Dynamics (6 units)
PHYS3039 Climate Dynamics (6 units)
PHYS3102 Advanced Electromagnetism (6 units)
PHYS3106 Nuclear Technologies and Applications (6 units)
STAT3004 Stochastic Processes (6 units)
STAT3015 Generalised Linear Modelling (6 units)
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