University of Malta

What you'll study

The programme combines advanced core topics in pure and applied mathematics with options that allow specialisation. Typical taught modules cover areas such as:

• Real and complex analysis — advanced measure theory, functional analysis and complex variable techniques for rigorous analysis and PDE theory.
• Algebra and geometry — group theory, ring and module theory, and introductory algebraic topology or differential geometry depending on pathway.
• Ordinary and partial differential equations — theory and methods for solving linear and nonlinear problems with applications in physics and engineering.
• Numerical analysis and scientific computing — numerical methods for linear algebra, approximation theory, finite element/finite difference approaches and error analysis, often with programming assignments.
• Probability, statistics and stochastic processes — advanced probability, statistical inference, stochastic modelling and time series for applied projects.
• Mathematical modelling and optimisation — techniques for formulating and analysing models from science, engineering, finance and operations research.

In addition to taught modules, the programme includes an independent research project or dissertation supervised by a member of the Department of Mathematics. The dissertation allows you to pursue a topic in pure mathematics, applied analysis, computational mathematics or an interdisciplinary area in collaboration with other departments or external partners.

Entry requirements

Applicants are normally expected to hold a relevant honours degree (or recognised equivalent) in mathematics, applied mathematics, statistics, engineering, physics or a closely related quantitative subject. Typical successful applicants will have a strong performance in mathematical subjects during their undergraduate studies.

• Academic qualifications: an undergraduate degree with substantial mathematical content. Specific grade expectations follow the University of Malta's standard admission policies and equivalence assessments for international qualifications.
• Supporting documents: academic transcripts, a curriculum vitae, and usually at least one academic reference.
• Language: proof of proficiency in English is required for applicants whose first language is not English, in line with the university's general regulations.
• Additional requirements: some applicants may be invited for an interview or asked to provide a short statement of research interests, particularly for research-focused pathways.

Career prospects

Graduates from this Master's programme enter a wide range of careers that value high-level quantitative and analytical skills. Common destinations include:

• Research and doctoral study in mathematics, applied mathematics or related sciences.
• Data science, machine learning and analytics roles across private sector companies and public organisations.
• Financial services and risk modelling, including quantitative analyst and actuarial pathways.
• Engineering and technology roles requiring mathematical modelling and numerical simulation.
• Education and teaching at secondary or post-secondary levels, subject to any local teacher certification requirements.
• Scientific computing, software development and consultancy work that leverages algorithmic and modelling expertise.

Why study at University of Malta

The University of Malta is the national higher-education institution with an established Department of Mathematics that offers a balanced combination of theoretical rigour and applied training. Studying here gives you access to experienced academic staff who supervise research projects across pure and applied areas, small-group teaching, and opportunities to collaborate with neighbouring departments such as Physics, Computer Science and Engineering.

Students benefit from the University's links with local industry and regional research networks, enabling applied projects with public and private partners. The campus environment and moderate cohort sizes support close supervision of dissertations and a supportive learning community for developing advanced mathematical expertise.