University of Siena

What you'll study

This programme provides a combination of theoretical and computational training in modern applied mathematics. Core areas typically include numerical analysis, partial differential equations, optimisation, scientific computing, stochastic processes and mathematical modelling. Students learn to translate problems from physics, engineering, biology, finance and data science into mathematical form and to design, analyse and implement efficient algorithms for their solution.

• Core modules — Numerical Methods for Differential Equations, Advanced Linear Algebra, Mathematical Modelling, Optimisation and Control, Computational Methods.
• Optional/specialist modules — Stochastic Processes and Applications, Inverse Problems and Data Assimilation, Scientific Machine Learning, Computational Finance, Mathematical Imaging.
• Computing and software — training in scientific programming (Python, MATLAB, C++), high-performance computing techniques and software for numerical simulation.
• Research project / dissertation — an extended research or applied project carried out under faculty supervision; topics can be drawn from collaborations with engineering, physics, life sciences or industry partners.
• Teaching format — a mix of lectures, problem classes, laboratory/computing sessions and seminars; assessment typically combines exams, coursework, project reports and oral presentations.

Entry requirements

Applicants are expected to hold a recognised undergraduate degree (three-year or equivalent) in mathematics or a related discipline such as physics, engineering, computer science or statistics, with substantial mathematics content. The admissions decision is based on academic transcripts, curriculum vitae and, where required, a personal statement describing mathematical background and research or career aims.

• Academic background — solid preparation in calculus, linear algebra, differential equations, and basic probability/statistics; prior exposure to numerical methods or scientific computing is desirable.
• Documentation — degree certificate and transcript, CV, and a statement of purpose. Some applicants may be asked for one or two academic references.
• Language — proficiency in the language of instruction is required; the programme may offer courses in English and/or Italian, so applicants whose first language is not the language of instruction will need to provide evidence of proficiency.
• Additional assessment — in some cases an interview or written assessment may be requested to establish suitability for the programme.

Career prospects

Graduates acquire skills that are in demand across a wide range of sectors. Common career paths include quantitative analyst and modeller roles in finance and insurance, data scientist or machine learning engineer positions, roles in engineering firms working on simulation and optimisation, and positions in energy, telecommunications, life sciences and environmental modelling. The degree also prepares students for doctoral research and academic careers in applied mathematics, computational science and interdisciplinary research programmes.

Why study at University of Siena

The University of Siena combines a long academic tradition with active research groups in numerical analysis, optimisation and applied probability. The department offers close interaction between students and faculty, collaborative projects with engineering and science departments, and opportunities to work on applied problems with local and international research partners. Located in a historic city, the university provides a supportive environment for focused study and access to regional industries and research networks that frequently collaborate on applied mathematics projects.