PhD student in Applied Mathematics, Ref PAR 2021/1734

The University of Gothenburg tackles society’s challenges with diverse knowledge. 53 500 students and 6 500 employees make the university a large and inspiring place to work and study. Strong research and attractive study programmes attract scientists and students from around the world. With new knowledge and new perspectives, the University contributes to a better future.

At the Division of Applied Mathematics and Statistics we conduct research at a high international level in areas such as Computational mathematics, Optimization, Mathematical statistics, Biomathematics, Bioinformatics, and Kinetic theory.

More information about our research groups is available on the website http://www.chalmers.se/en/departments/math/research/research-groups/ 

We have an international environment with frequent exchanges with other universities around the world. The department provides a friendly, creative, and supportive atmosphere with a steady flow of international guests. At the division there are many committed teachers with extensive and broad experience of all aspects of higher education. Together with the Divisions of Algebra and Geometry and Analysis and Probability we form the academic part of the department of Mathematical Sciences, which is a joint department of Chalmers and the University of Gothenburg, and one of the largest in mathematics in the Nordic countries.

More information about us is available on the website http://www.chalmers.se/en/departments/math/

Our department continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all our activities. We work actively to be a parent-friendly organization.

The announced PhD position, which is located at the Division of Applied Mathematics and Statistics, is supervised by Professor Larisa Beilina.

Job assignments
The work will be performed in a dynamic research environment at the interface between mathematics and computational electromagnetics.  Mathematical analysis and computational experiments will be closely integrated as the major tools in developing an adaptive finite element method for solving the time-dependent Maxwell equations. 

The project will offer you training in a wide range of front-line computational methods. This PhD program will prepare you for a range of career opportunities in academia as well as in private and public sectors. Postgraduate education consists of four years of full-time studies and leads to a PhD degree.

The total period of employment may not exceed the equivalent of four years of full-time postgraduate education and may be extended after institutional service, e.g., teaching, by a maximum of 20% in accordance with HF 5, section 5, section 7, doctoral student employment.

Specific subject description
The aim of the project is to find numerical solutions of the coefficient inverse problem (CIP) for Maxwell’s equations. The theoretical task is to develop and analyse adaptive finite element method for  CIP. The methodology is then applied to measurements of an electrical field, for example to microwave medical imaging. A more detailed description can be found on http://www.math.chalmers.se/~larisa/www/PhD_CNRS/PhD_GU2021.pdf

Eligibility
Applicants for the position should have a master’s degree (or a 4-year bachelor's degree) in Mathematics, Physics, Computer Science, or a related discipline, awarded by an internationally recognized university-level institution prior to the start of the employment.

The candidate should be familiar with partial differential equations and be genuinely interested in biomedical and engineering applications. Familiarity with numerical methods and C++ programming is an advantage.

As the work will be conducted in a multi-cultural and multi-disciplinary environment, cultural awareness and good collaboration skills are important. It is equally important that you are a well-organized and autonomous person. Sound verbal and written communication skills in English are required.

For further information regarding the position
Annika Lang, Professor, Head of Unit of Applied mathematics and statistics
+46 31 772 5356, [email protected]

Larisa Beilina, Professor
+46 31 772 3567, [email protected]

Read more about the position and apply here
Closing date: 2022-02-26

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