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.
News & Current Opportunities
Guest Program
Call for proposals for the Romberg Visiting Professor and Romberg Visiting Scholar 2027
Deadline: June 30, 2026
26.05.2026
10:00 - 11:30
10:00 - 11:30
Theory & Methods
Getting started with generative AI coding tools
Compact Courses
Speaker: Dr. Inga Ulusoy, Research Software Engineer, Scientific Software Center (SSC)
Location: Mathematikon • Conference Room, Room 5/104, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register on the course website
Organizer: Scientific Software Center (SSC)
Location: Mathematikon • Conference Room, Room 5/104, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register on the course website
Organizer: Scientific Software Center (SSC)
ECTS: 0.5
This compact course is part of the course program of the Scientific Software Center (SSC) at Heidelberg University.
The latest information and a registration link are available on the course website.
The latest information and a registration link are available on the course website.
Prerequisites
Basic Python knowledge is required. Participants need a laptop/PC with Visual Studio Code installed. Participants need to have access to GitHub copilot (either through free trial, individual license such as GitHub student (free), or other form of license).
Summary
Generative AI is emerging as a major creative force that supports humans in content creation. AI coding tools can support software development on many levels. In this short course, participants will get started with using GitHub copilot in VSCode as effective coding tools.
Learning Objectives
After the course participants will be able to
- Connect to GitHub Copilot for AI-assisted coding
- Use AI-assistance in a coding environment
- Know some limitations of these tools
- Know some legal and ethical implications
- Know some privacy and security concerns in the use of such tools
Basic Python knowledge is required. Participants need a laptop/PC with Visual Studio Code installed. Participants need to have access to GitHub copilot (either through free trial, individual license such as GitHub student (free), or other form of license).
Summary
Generative AI is emerging as a major creative force that supports humans in content creation. AI coding tools can support software development on many levels. In this short course, participants will get started with using GitHub copilot in VSCode as effective coding tools.
Learning Objectives
After the course participants will be able to
- Connect to GitHub Copilot for AI-assisted coding
- Use AI-assistance in a coding environment
- Know some limitations of these tools
- Know some legal and ethical implications
- Know some privacy and security concerns in the use of such tools
27.05.2026
09:00 - 13:00
09:00 - 13:00
Theory & Methods
Sustainability in Research Software for HPC Format
Compact Courses
Speaker: Dr. Andreas Baer • KIT
Location: Mathematikon • Conference Room, Room 5/104, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register on the course website
Organizer: Scientific Software Center (SSC)
Location: Mathematikon • Conference Room, Room 5/104, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register on the course website
Organizer: Scientific Software Center (SSC)
ECTS: 0.5
This compact course is part of the course program of the Scientific Software Center (SSC) at Heidelberg University.
The latest information and a registration link are available on the course website.
The latest information and a registration link are available on the course website.
Prerequisites
No prerequisites, but some experience with running codes on HPC or writing software for HPC is helpful.
Summary
Maximal performance! This used to be the goal for research software for HPC, but sustainability is getting more and more traction and growing importance. This course targets two aspects contributing to sustainable research software for HPC clusters: Firstly, energy and carbon optimization in the usage is outlined to raise awareness and make the participants ready for future HPC systems with energy-budget-based resource grants or efficiency rewarding queuing systems as pioneered by Japans #1 supercomputer Fugaku. Secondly, sustainability in the development process of HPC research software is addressed, where productivity, code quality and carbon efficiency often go hand in hand. The course is specifically targeted to researchers using and developing HPC research software, in all career stages, irrespective of their usage type (e.g. physical simulations, data analysis, AI). It is intended as an interactive course, allowing plenty of time for discussion and exchange on this topic.
No prerequisites, but some experience with running codes on HPC or writing software for HPC is helpful.
Summary
Maximal performance! This used to be the goal for research software for HPC, but sustainability is getting more and more traction and growing importance. This course targets two aspects contributing to sustainable research software for HPC clusters: Firstly, energy and carbon optimization in the usage is outlined to raise awareness and make the participants ready for future HPC systems with energy-budget-based resource grants or efficiency rewarding queuing systems as pioneered by Japans #1 supercomputer Fugaku. Secondly, sustainability in the development process of HPC research software is addressed, where productivity, code quality and carbon efficiency often go hand in hand. The course is specifically targeted to researchers using and developing HPC research software, in all career stages, irrespective of their usage type (e.g. physical simulations, data analysis, AI). It is intended as an interactive course, allowing plenty of time for discussion and exchange on this topic.
28.05.2026
09:00 - 13:00
09:00 - 13:00
Theory & Methods
Generative AI for writing (research) software
Compact Courses
Speaker: Dr. Inga Ulusoy, Research Software Engineer, Scientific Software Center (SSC)
Location: Mathematikon • Seminar Room 11, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register on the course website
Organizer: Scientific Software Center (SSC)
Location: Mathematikon • Seminar Room 11, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register on the course website
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.
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 need a laptop/PC with Visual Studio Code installed and a working Python environment. Participants need to have access to GitHub copilot (either through free trial, individual license such as GitHub student (free), or other form of license).
Summary
Generative AI is emerging as a major creative force that supports humans in content creation. Specifically trained models can support software developers with their software projects and lead to time savings and a shift in what aspects of generating software are more important on a day-to-day basis. In this course, we will learn how to set up and use AI tools in software development projects. Best practices in using such tools, as well as recommendations how to use them efficiently and safely will be introduced.
Learning Objectives
After the course participants will be able to
- Use AI-assistance in a coding environment
- Know about the limitations of these tools
- Be aware of legal and ethical implications
- Be aware of privacy and security concerns in the use of such tools
Basic Python knowledge is required. Participants need a laptop/PC with Visual Studio Code installed and a working Python environment. Participants need to have access to GitHub copilot (either through free trial, individual license such as GitHub student (free), or other form of license).
Summary
Generative AI is emerging as a major creative force that supports humans in content creation. Specifically trained models can support software developers with their software projects and lead to time savings and a shift in what aspects of generating software are more important on a day-to-day basis. In this course, we will learn how to set up and use AI tools in software development projects. Best practices in using such tools, as well as recommendations how to use them efficiently and safely will be introduced.
Learning Objectives
After the course participants will be able to
- Use AI-assistance in a coding environment
- Know about the limitations of these tools
- Be aware of legal and ethical implications
- Be aware of privacy and security concerns in the use of such tools