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
More information about our research groups is available on the website
https:// 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
More information about us is available on the website
https:// 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.
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
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
https:// www. math.chalmers.se/~larisa/www/PhDCNRS/PhDGU2021.pdf
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@example.com
Larisa Beilina, Professor
+46 31 772 3567, firstname.lastname@example.org
Read more about the position and apply here
Closing date: 2022-02-26