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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...]

01.09.2025 - 05.09.2025
Practicals & Schools
European Conference on Numerical Mathematics and Advances Applications (ENUMATH 2025)
Conference

Speaker: Various Speakers
Location: Heidelberg
Registration: Please register on the event website
ECTS: 2
The European Conference on Numerical Mathematics and Advanced Applications (ENUMATH) conferences are a forum for presenting and discussing novel and fundamental advances in numerical mathematics and challenging scientific and industrial applications on the highest level of international expertise.

For more information, please visit the event website.

As members of the University of Heidelberg, those of you who would like to participate can contact us at enumath2025@uni-heidelberg.de to receive a voucher to have the participation fee waived. Note that the voucher is required during the registration process, so make sure you register after having received one.

Conference Themes
• Advances in Discretisation Schemes
• Multiscale and Multiphysics Problems
• Hardware-Aware Scientific Computing
• Inverse Problems
• Uncertainty Quantification 
• Data-Driven Modelling and Simulation
• Scientific Machine Learning
• Reduced Order Models and Surrogates
• Randomised Numerical Algorithms
• Numerical Optimisation and Optimal Control

For more information, please visit the event website.
 
15.09.2025 - 17.09.2025
Theory & Methods
HGS MathComp Annual Retreat 2025
Networking

Location: Würzburg, Germany
Registration: Please register on the event website • Registration open until July 20, 2025
Organizer: HGS MathComp
ECTS: 2
The Fellow Speakers of HGS MathComp invite all current and prospective fellows to this year’s annual retreat in Würzburg. The retreat offers a unique opportunity to connect with other fellows from diverse fields of scientific computing, present your own work, and learn about others’ research through short pitches. Social activities like a fun pub quiz will complete the experience.

The HGS MathComp Annual Retreat will go on for 2.5 days and will feature workshops to improve academic practice and chances for our Fellows to present their current research.

More information and a detailed program is available on the website of the HGS MathComp Annual Retreat.

Sharpen your skills in software development courses and poster design/presentation. Explore career paths beyond academia by engaging with HGS MathComp alumni now working at leading companies such as AbbVie, Apple, Merck and Carl Zeiss.
 
15.09.2025 - 19.09.2025
Practicals & Schools
IWR School "Machine Learning for Fundamental Physics"
School

Location: Mathematikon • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register on the event website
Organizer: IWR
ECTS: 3
The 2025 IWR School on Machine Learning for Fundamental Physics is aimed at advanced PhD students specializing in scientific machine learning. We particularly encourage registrations from researchers with experience in scientific machine learning, as demonstrated by papers or preprints related to the topic of the school.

More information on the event website

Machine Learning is here to stay and is shaping the future of fundamental physics research. From optimal inference, over theory-inspired network architectures, to anomaly detection, representation learning and foundation models, a new generation of scientists is driving these exciting developments. This school aims to further strengthen technical expertise and foster new connections.

Central themes of the school are:

- Modern network architectures
- Precision and uncertainties
- Scientific foundation models
- Generative Networks
- Representation learning
- Optimal inference
- Quantum field theory and networks

2025 lecturers:

- Thea Aarrestad (ETH Zurich) -- Particle experiments, anomalies
- Jim Halverson (Northeastern University) -- Particle theory, KANs
- Michael Kagan (SLAC) -- Representation learning, foundation models
- Siddharth Mishra-Sharma (Anthropic, Boston University) -- Cosmological analyses
- Veronica Sanz (University of Valencia) -- ML for data mining
- David Shih (Rutgers University) -- Linking particle and astrophysics
- Ramon Winterhalder (University of Milan) -- Generative Networks