Skip to main navigation Skip to main content Skip to page footer
My Site Package My Site Package

HGS MathComp - Where Methods Meet Applications

The Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences (HGS MathComp) at Heidelberg University is one of the leading graduate schools in Germany focusing on the complex topic of Scientific Computing. Located in a vibrant research environment, the school offers a structured interdisciplinary education for PhD students. The program supports students in pursuing innovative PhD projects with a strong application-oriented focus, ranging from mathematics, computer science, bio/life-sciences, physics, and chemical engineering sciences to cultural heritage. A strong focus is put on the mathematical and computational foundations: the theoretical underpinnings and computational abstraction and conception.

HGS MathComp Principal Investigators are leading experts in their fields, working on projects that combine mathematical and computational methodology with topical research issues. Individual mentoring for PhD candidates and career development programs ensure that graduates are fully equipped to take up top positions in industry and academia.

Upcoming Events [see all...]

03.07.2025
15:45 - 16:15
HGS MathComp Mixer
Networking

Location: Mathematikon • Common Room, 5th Floor • Im Neuenheimer Feld 205 • 69120 Heidelberg
Organizer: HGS MathComp
ECTS: 0
Join us for an informal get-together of the HGS MathComp community just before the IWR Colloquium. Bring your colleagues, have some cake and beverages, and find out what's currently going on in the other research groups.
 
03.07.2025
16:15
Theory & Methods
Inference of Constitutive Relations From Data, With Application to Sea Ice Modeling
IWR Colloquium

Speaker: Prof. Georg Stadler • Courant Institute, New York University, USA • 2024 Romberg Visiting Scholar
Location: NeMathematikon • Lecture Hall, Ground Floor • Im uenheimer Feld 205 • 69120 Heidelberg
Registration: No registration required
Organizer: Interdisciplinary Center for Scientific Computing (IWR)
ECTS: 1 for 5
The IWR Colloquium serves as a platform for the interdisciplinary dialogue which characterizes the field of scientific computing. Every semester, members of the IWR and its affiliated institutions as well as renowned international experts are invited to present their latest scientific results and discuss the upcoming challenges in the field of scientific computing.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom. For more information please visit the website of the colloquium.

Sea ice is a fundamental component of the climate system and is typically treated as a continuum fluid. The most widely used sea-ice model today, proposed by Hibler in 1979, was developed from heuristic analytical arguments. Although reliable in regions of high ice concentration, it performs poorly elsewhere. In this talk, we present a general framework for inferring constitutive relations from data, and apply it to sea ice. The approach uses a characterization of isotropic constitutive laws as scalar functions of the principal invariants of the strain-rate tensor. These scalar functions are represented by neural networks trained on data generated by a Lagrangian discrete element model. By coupling PyTorch with the finite-element package Firedrake, we incorporate the governing PDE into the training process, which requires solving a PDE-constrained optimization problem for the network parameters.
 
08.07.2025
09:30 - 13:00
Theory & Methods
Effective software testing
Compact Courses

Speaker: Dr. Liam Keegan, Research Software Engineer, Scientific Software Center (SSC)
Location: Mathematikon • Room 5/104, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register via this form
Organizer: Scientific Software Center (SSC)
ECTS: 0.5
This is a half day course.

The latest information and a registration link are available on the course website.

This compact course is part of the course program of the Scientific Software Center (SSC) at Heidelberg University.

Prerequisites:
Basic Python knowledge is required. Participants are recommended to bring a laptop.

Summary:
A good test suite makes extending, maintaining and debugging a codebase both easier and faster. In this course we will look at the different kinds of tests, and understand how to write good tests. We will also cover different testing strategies, such as test-driven-design when writing new code, or acceptance testing when working with legacy code that doesn’t have a good test suite. Code samples will use the Python testing framework pytest but the concepts also apply to other frameworks and languages.

Learning Objectives:
After the course participants will
- Understand the different kinds of tests
- Understand different testing strategies
- Write better tests of their code
- Deal better with legacy code that is missing tests