KTH Royal Institute of Technology

Overview

The PhD programme in Applied and Computational Mathematics at KTH Royal Institute of Technology is designed to cultivate advanced research skills in the fields of mathematical statistics, numerical analysis, and optimization theory. Students will engage with experienced supervisors and collaborate with research groups associated with the Stockholm Mathematics Center (SMC), fostering a vibrant academic environment.

What you'll study

The doctoral programme is structured around three primary research areas:

• Mathematical statistics
• Numerical analysis
• Optimization theory and system theory

Your studies will harmoniously blend coursework with research supervision, typically including:

• Core doctoral courses: These will cover essential topics such as probability theory, numerical methods for partial differential equations, numerical linear algebra, and convexity in linear spaces.
• Area-specific courses: Tailored to your research focus, these may include stochastic modelling, inverse problems, numerical optimisation, and systems and control theory.
• Research seminars and academic training: Designed to enhance your research communication skills and professional development.
• Thesis work: Focused on producing a doctoral dissertation based on original research contributions.

The selection of courses is customized according to your academic background and research interests, formalized in your individual study plan in consultation with your supervisors.

Entry requirements

To be eligible for admission, candidates must meet KTH’s general entry requirements for doctoral studies. This typically necessitates possessing a relevant second-cycle (Master’s level) qualification or an equivalent level of knowledge gained through other means.

Career prospects