University of Zurich

Overview

The PhD in Computational Science at the University of Zurich offers a unique opportunity to engage in independent research while following a structured doctoral curriculum. This program is designed to prepare students for careers in academia, industry, and research by providing a solid foundation in computational science and hands-on experience in advanced research methodologies.

What you'll study

The program encompasses a personalized curriculum that includes a minimum of 12 ECTS credits, tailored to align with your research interests and strengthen your computational science knowledge. The coursework covers essential topics such as:

• Computational Thinking
• High Performance Computing
• Academia–Industry Modeling Week
• Retrieving Geographic Information
• Computational Mathematics

In addition to coursework, students are encouraged to participate in weekly research seminars, attend at least one scientific congress or summer school each year, and gain teaching experience through a minimum of one teaching load per semester. These elements foster a comprehensive academic development experience.

Dissertation

The culmination of the program is a written doctoral dissertation based on your independent research project. The topic and supervision are defined within the doctoral framework and require approval from the relevant faculty.

Entry requirements

To gain admission to the PhD program, candidates must meet the following criteria:

• A Master’s degree from an accredited university or an equivalent qualification.
• Approval of the PhD project by a professor at the Faculty of Science or another qualified individual authorized to confer a PhD.
• Proof of sufficient English proficiency, typically demonstrated by a minimum TOEFL iBT score of 100 or an IELTS score of 7.0, for those whose native language is not English.

Additional application materials may include academic transcripts, degree certificates, and documentation demonstrating research fit, with specific requirements varying by applicant and faculty.

Career prospects