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.
Location: Mathematikon • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register on the event website • Registration open until June 15, 2026
Organizer: IWR
The school offers a comprehensive overview of key topics in Artificial Intelligence and Machine Learning, including Generative AI, Explainability, Simulation-Based Inference, Agentic AI, Robustness and Validation of AI Methods, Vision-Language Models, Self-Supervised Learning, Knowledge Integration, and Causality. In addition to expert lectures, the program features hands-on sessions and best-practice sessions focused on how to use the latest AI tools in research.
Participants are expected to have a solid understanding of the core concepts of machine learning.
For more information, please visit the event website.
Registration: Please register on the event website • Registration open until June 30
Participants can expect a mix of lectures and interactive sessions that provide insight into the mathematical foundations as well as real-world use cases of graph-based machine learning methods.
A tentative schedule will be released soon, where all relevant organizational details will also be provided.
- a poster session and networking dinner on the first day
- a social event
- hands-on tutorials with a focus on applications
- sessions combining theoretical perspectives with practical examples
Speakers:
- Jan Stühmer (HITS, KIT) – Introduction to GNNs, including a practical session, and Equivariance as Design Principle in Modern Machine Learning
- Ismail Ilkan Ceylan (TU Vienna, AITHYRA) – Graph Foundation Models
- Joel Oskarsson (ETH) – GNNs for Spatio-Temporal Modelling and Earth System Modelling
- Arghya Bhowmik (DTU) – GNNs for Material Sciences
10:00 - 17:00
Location: Online
Registration: Please register on the course website
Organizer: Graduate Academy
Course times:
23.09.2026: 9:30–16:30
24.09.2026: 9:30–16:30
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.
During the workshop, participants work with their own texts as well as with examples from their own disciplines that they bring along and consider to be particularly well written. They discuss features of good scientific papers and are equipped to use adequate language in different genres and for different audiences. In addition, they receive peer feedback on their own drafts. All exercises empower them to produce clearer, and more correct, concise, and reader-oriented papers.
The two-day workshop covers the following topics:
• taking inventory: participants‘ strengths and challenges in writing scientific papers in English
• a brief introduction to research and writing processes
• using text analysis to become a better writer
• reporting findings, ideas, and opinions professionally and adequately
• making yourself understood: principles of clear and concise writing
• structuring ideas, organising texts: transitions, connectives, & co.
• working effectively with co-authors and constructive text feedback
• useful online and offline resources
(After the workshop, participants have the opportunity to sign up for an individual writing coaching, or text feedback session. In this session, they can ask for individual feedback on an extract of their written work, or get deeper into issues from the workshop in a one-on-one setting.)