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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...]

16.04.2024 - 17.04.2024
09:00 - 17:00
Key Competences
Conference Presentation - Engaging the Listener in Your Talk
Compact Courses
Speaker: Julie Stearns, impulsplus
Location: In-person event, Heidelberg
Registration: Please register on the event website
Organizer: Graduate Academy
Date & time:
16.04.2024 • 09:00 - 17:00
17.04.2024 • 09:00 - 17:00

This course is part of the course program of the Graduate Academy.

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

Target group

This workshop is designed for doctoral candidates with previous presentation experience.


"Wow, that presenter is so good in front of an audience. If only that were easier for me!" Being a good speaker is often just a question of developing a set of skills and techniques. The use of voice and body language, an effective presentation structure and the dynamic use of language require awareness and practice. The workshop helps to identify and explore these requirements, from self-reflection to self-assurance and long-term excellence.


This seminar provides participants the opportunity to improve their conference presentation skills. Constructive feedback from the trainer and group members give the speaker a healthy amount of input while practicing new ideas and techniques to enhance the quality of their speech and overall impact of the talk.

Participants will be required to prepare a 3 to 5 minute overview of their work; the use of slides is optional. This will provide a basis for applying the practical aims of the workshop.

Throughout the two-day workshop, participants will be guided through interactive exercises to improve non-verbal communication, improve the ability to listen and react generously, and to integrate focusing techniques, which empower the speaker. Attention will also be given to structural and language aspects to improve clarity and flow of the talk.

Contents in Brief

- Effectively introducing yourself
- Engaging the audience in your talk
- Affirming the strengths and individual style of the speaker
- Improving body language and vocal quality
- Structuring your talk
- Constructive tactics for dealing with nervousness
- Dealing with challenging questions (Q&A sessions)
- Networking at conferences


- Voice and body techniques
- Partner work
- Language practice and analysis
- Interactive activities with online tools
- Videotaping and feedback sessions
18.04.2024 ff
13:00 - 17:00
Key Competences
Introduction to programming with Python
Compact Courses
Date & time:
18.04.2024 • 13:00 - 17:00
25.04.2024 • 13:00 - 17:00
02.05.2024 • 13:00 - 17:00

No previous programming knowledge is required! We will use our own server platform for the course, therefore no additional installation of software is needed.

This course is part of the course program of the Graduate Academy. 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

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.
22.04.2024 - 25.04.2024
09:00 - 12:30
Theory & Methods
Romberg Course: Analytical Methods for Bayesian Inverse Problems Related to Partial Differential Equations
Compact Courses
Speaker: Prof. Dr. Antonio Capella Kort • National Autonomous University of Mexico (UNAM) • Romberg Visiting Professor
Location: Mathematikon • Seminar Room 11, 5th floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register here
Organizer: HGS MathComp
This course is part of the HGS MathComp Romberg Visiting Professor Program.

This lecture presents some basic topics on probability, Bayesian statistics theory, analytical results on partial differential equations (PDEs) and inverse problems. The combination of these methods led to general approaches that can be used to derive efficient and robust approximations to solve inverse problems with uncertainty quantification. By the end of this course, students will gain insights into how these methods contribute to providing more accurate and reliable schemes to solve inverse problems with uncertainty quantification.

In the practice sessions, we present specific inverse problems, allowing the students to actively engage with the material and develop practical solutions through coding exercises.


- Introduction: mathematical models and inverse problems.
- Basic topics in probability theory and functional analysis.
- Inverse problems, Bayesian inference and uncertainty quantification.
- Existence and consistency (stability) of posterior distributions.
- Exploring the posterior and sampling methods.
- Stability estimates for linear PDEs and physically informed models.

- Day 1: 2 x 90 minutes sessions
- Day 2 to 4: 1 90 minutes session + 1 90 minutes practice session