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.
15.07.2026
09:00 - 13:00
09:00 - 13:00
Theory & Methods
Expert Topics in Version Control with Git
Compact Courses
Speaker: Dr. Dominic Kempf, 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
Prior knowledge about version control with Git is required. This can e.g. be acquired by attending the SSC’s introductory course “Version Control with Git” and “Intermediate Topics in Version Control with Git”. This course is intended for researchers that develop their own research software. Participants are required to bring their own laptops to work on during the course. Network access (e.g. through Eduroam) is recommended.
Summary
Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop explores some advanced topics that increase the participants’ repertoire of Git workflows: Bisection, Worktrees, Submodules, Large File Storage and Pre-commit Hooks. Additionally, we showcase invasive methods of modifying a Git repository via Rebase.
Learning Objectives
After the course participants will
- Know about advanced Git features like submodules, large file storage
- Be able to bisect regression in a Git repository
- Understand the advantages of worktrees
- Be able to apply pre-commit hooks for their Git repositories
- Have used Rebase to change a repository’s Git history
Prior knowledge about version control with Git is required. This can e.g. be acquired by attending the SSC’s introductory course “Version Control with Git” and “Intermediate Topics in Version Control with Git”. This course is intended for researchers that develop their own research software. Participants are required to bring their own laptops to work on during the course. Network access (e.g. through Eduroam) is recommended.
Summary
Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop explores some advanced topics that increase the participants’ repertoire of Git workflows: Bisection, Worktrees, Submodules, Large File Storage and Pre-commit Hooks. Additionally, we showcase invasive methods of modifying a Git repository via Rebase.
Learning Objectives
After the course participants will
- Know about advanced Git features like submodules, large file storage
- Be able to bisect regression in a Git repository
- Understand the advantages of worktrees
- Be able to apply pre-commit hooks for their Git repositories
- Have used Rebase to change a repository’s Git history
15.07.2026
13:00 - 14:00
13:00 - 14:00
Upstream Lunch Break
Networking
Speaker: TBA
Location: Mathematikon • Room 5/200, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Organizer: UPSTREAM – The Network for Women in Science, Engineering, Mathematics and Computer Science at Heidelberg University
Location: Mathematikon • Room 5/200, 5th Floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Organizer: UPSTREAM – The Network for Women in Science, Engineering, Mathematics and Computer Science at Heidelberg University
ECTS: 0
The Upstream program is aimed at female mathematicians and scientists at all stages of their education, from pupils and students to doctoral candidates. Postdocs and professors will also find a lively network here, where the focus is on exchanging ideas about studying and careers in the STEM subjects.
The heart of Upstream is our monthly lunch break, which takes place every third Wednesday during the semester. We meet in the Common Room on the 5th floor of the Mathematikon and enjoy our lunch together. A delicious dessert is provided by us. We plan our future events, talk to guests from science or industry or simply chat about our studies.
The heart of Upstream is our monthly lunch break, which takes place every third Wednesday during the semester. We meet in the Common Room on the 5th floor of the Mathematikon and enjoy our lunch together. A delicious dessert is provided by us. We plan our future events, talk to guests from science or industry or simply chat about our studies.
16.07.2026 ff
13:00 - 17:00
13:00 - 17:00
Key Competences
Introduction to programming with Python
Compact Courses
Speaker: Boyana Boneva & Kevin Leiss • codeprehensible
Location: Online
Registration: Please register on the course website
Organizer: Graduate Academy
Location: Online
Registration: Please register on the course website
Organizer: Graduate Academy
ECTS: 1
This course is part of the course program of the Graduate Academy. Please note that this course will be held in English.
Course Dates:
16.07.2026, 13:00–17:00
23.07.2026, 13:00–17:00
30.07.2026, 13:00–17:00
The latest information and a registration link are available on the course website (log in with Uni-ID).
HGS MathComp fellows can get a reimbursement of the course fees. Please submit your proof of payment and certificate of participation to hgs@iwr.uni-heidelberg.de.
Course Dates:
16.07.2026, 13:00–17:00
23.07.2026, 13:00–17:00
30.07.2026, 13:00–17:00
The latest information and a registration link are available on the course website (log in with Uni-ID).
HGS MathComp fellows can get a reimbursement of the course fees. Please submit your proof of payment and certificate of participation to hgs@iwr.uni-heidelberg.de.
This course introduces the general-purpose programming language Python, which is used by web developers, data scientists and machine learning experts. Understanding the basics of Python will allow you to grasp the concepts of tools you might encounter and quickly apply them to your own research.
Within the scope of this course, you will master the Python philosophy, syntax, and writing your own scripts and modules. In addition, you will use your newly acquired skills to perform hands-on exercises and learn to conduct reproducible in-silico research. After completing this course, you will be ready to start your own Python journey and delve deeper into the world of Data Science.
Requirements: No previous programming knowledge is required! We will use our own server platform for the course, therefore no additional installation of software is needed.
Within the scope of this course, you will master the Python philosophy, syntax, and writing your own scripts and modules. In addition, you will use your newly acquired skills to perform hands-on exercises and learn to conduct reproducible in-silico research. After completing this course, you will be ready to start your own Python journey and delve deeper into the world of Data Science.
Requirements: No previous programming knowledge is required! We will use our own server platform for the course, therefore no additional installation of software is needed.