Summary
The Mathematics of Computational Science group at the University of Twente is inviting applications for a 1.5-year postdoc position focused on adaptive space-time methods for time-dependent partial differential equations. This role offers an opportunity to engage in cutting-edge research under the supervision of Dr. Gregor Gantner.
Postdoc Position in Numerical Analysis, University of Twente, Netherlands
Designation
Postdoc in Numerical Analysis
Job Table
| Attribute | Details |
|---|---|
| Hours | 40 hours/week |
| Salary | €3,546 – €5,538 gross/monthly based on full-time |
| Deadline for Application | May 20, 2026 |
| Location | University of Twente, The Netherlands |
Research Area
Adaptive methods for time-dependent partial differential equations (PDEs), specifically focusing on space-time finite element and boundary element methods.
Eligibility/Qualification
- PhD degree in Applied Mathematics or a closely related field.
- Strong focus on numerical methods for partial differential equations.
- Familiarity with:
- Adaptive finite element methods
- Boundary element methods
- Space-time methods
- Proficiency in programming (Matlab, Python, Julia, or C/C++).
- Strong analytical and creative mindset, with a team-oriented attitude.
- Fluent in English.
Job Description
You will be responsible for:
- Advancing the field of adaptive space-time methods.
- Designing, analyzing, and implementing numerical algorithms for parabolic PDEs (e.g., heat equation).
- Developing a-posteriori computable estimators for discretization error and guiding mesh refinement.
- Validating theoretical results through numerical experiments.
- Conducting research in a collaborative interdisciplinary environment, promoting academic excellence.
How to Apply
Interested candidates should apply online by clicking the ‘Apply now’ button, submitting a CV and motivation letter before the deadline. For inquiries, you may contact Dr. Gregor Gantner at gregor.gantner@utwente.nl.
Last Date for Apply
May 20, 2026
Join us at the University of Twente and contribute to innovative research in computational science!
