Bachelor of Mathematics (Industrial and Applied Mathematics)

Entry requirements

Duration
3 YEAR(S) FULL-TIME
Scholarship
NO
Fee
AUD$ 37,100 PER ANNUM
Intake
FEBRUARY JULY

English language entry requirements

In addition to meeting academic entry requirements, international students who speak English as a second or additional language must also meet the University's English language entry requirements. The minimum language requirements for this program are:

English language test

IELTS total [6.0]

IELTS reading [6.0]

IELTS writing [6.0]

Admission Requirements by Country-2.71

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Degree overview

Develop your problem solving and analytical skills in modelling, optimisation, applied probability and differential equations.

Enjoy a diverse and flexible study program exploring the relationship and application of mathematics to areas such as physics, engineering, information technology and biology.

Graduate work-ready with sound knowledge in applied mathematics and strong multi-disciplinary skills.

Gain real-world experience with a major project or completion of the Maths Clinic program working closely with an industry partner.

Join an exceptional cohort of students learning from educators dedicated to training to next generation of mathematicians and data scientists.

Gain access to a diverse range of researchers in pure and applied mathematics working together to discover, understand, interpret and apply mathematics to important industrial and social problems.

Study at a university with research in the field of mathematical sciences, applied mathematics and statistics ranked well above world-class1.

Pursue a career in industry across a range of sectors or consider building your expertise with a research degree.

Career outcomes

Careers to consider:

Biostatistician: using or applying mathematics and statistics to various categories in biology; designing biological experiments primarily in the field of agriculture and medicine; collecting, dissecting, and summarising data and releasing information based on the findings of that data

Science and the environment: modelling in food security, climate change and weather forecasting and renewable energy solutions; use data analysis and mathematical modelling to make evidence-based decisions.

Health and society: modelling of infectious disease and making evidenced-based recommendations; biomedical engineering and data analysis; epidemiology.

Engineering and resources: modelling for more efficient minerals processing, particularly for rare minerals.

Business, marketing and finance: interpreting data to optimise processes and make effective decisions; forecasting; cryptocurrencies.

Technology: digitisation, automation, optimization of processes; artificial intelligence; using your logical thinking and creativity to solve problems.

Security and defence: modelling for defence optimisation; cybercrime

Transport and logistics: optimisation and managing strings of processes; infrastructure modelling.


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