Artificial Intelligence (AI) is now key to accelerating scientific discovery, engineering advancements and driving innovation and efficiency in business, government and other organisations.
Develop a deep understanding of mathematical concepts and techniques essential for AI, including statistics, linear algebra, calculus, numerical methods and advanced machine learning techniques like deep learning and optimisation.
Combining these mathematical methods with AI approaches means you’ll be able to effectively analyse complex data, develop AI models and automate decision-making processes.
The focus is on theoretical depth while also covering software development, preparing you for both academic research and industry needs.
Choose to combine your major with a minor in bioinformatics, computational science, computer science, physics, science communication or statistics.
You'll graduate ready for a range of careers in AI research, data science and machine learning engineering, driving innovation and solving real-world challenges across diverse industries.
Career possibilities
Our programs prepare you for your first job and beyond. Here are some of the careers you could be on your way to:
- Data scientist
- Business intelligence analyst
- Biostatistician
- Research engineer
- Statistical analyst
- Cyber security analyst
- Software developer
- Cryptographer
- Bioinformatics researcher
- Cyber systems engineer
Average annual salary range
Data Scientist
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Average annual salary range
Data Engineer
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Next steps after graduation
The Bachelor of Mathematics provides quantitative training that will set you apart in the job market and see you excel in mathematics or one of the many disciplines it influences.
With a degree in mathematics, you will be sought by industry for your excellent quantitative and problem-solving abilities, and gain a wide range of rewarding positions in the public and private sectors. This includes roles in:
- finance
- economics
- mathematical research
- statistics
- actuarial studies
- quantitative finance
- meteorology
- information technology
- data science
- AI research
- teaching.
The problem-solving skills I developed during my mathematics degree have been so widely applicable to the range of projects I have worked on in my undergraduate research and in my role as a Data Analyst Consultant.
Mathematics is a broad field of study, and I enjoy being exposed to its many sub-fields and being able to work out mathematical solutions with my classmates to problems I've grappled with for hours or days.
The problem-solving skills I developed during my mathematics degree have been so widely applicable to the range of projects I have worked on in my undergraduate research and in my role as a Data Analyst Consultant.
Mathematics is a broad field of study, and I enjoy being exposed to its many sub-fields and being able to work out mathematical solutions with my classmates to problems I've grappled with for hours or days.
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29 June
Queensland Biology Winter School, Year 12
1 July
International Baccalaureate Research Skills Program
Stories
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UQ people
Making the greatest mathematical discoveries
3-minute read
Study tips
UQ science scholarships to help fund your studies
8-minute read
Stories
See all storiesUQ people
Making the greatest mathematical discoveries
3-minute read
Study tips
UQ science scholarships to help fund your studies
8-minute read
How you'll learn
Your learning experiences are designed to best suit the learning outcomes of the courses you choose.
- Lectures
- Tutorials
- Work placements
- Research experience
- Seminars
- Workshops
What you'll study
At UQ, subjects are called 'courses'. Here's a sample of the courses you could study:
- Statistical Learning
- Numerical Linear Algebra and Optimisation
- Deep Learning
- Mathematical Statistics
- Probability Models & Stochastic Processes
- High-Performance Computing
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