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
24.06.2026
- 26.06.2026
Practicals & Schools
4EU+ Workshop on AI in Medicine: Generative and Foundation Models
Workshop
Location: Sorbonne Cluster for Artificial Intelligence • 4 Place Jussieu • 75005 Paris, France
Registration: Please apply on the event website • Application open until February 28, 2026
Organizer: Mannheim Institute for Intelligent Systems in Medicine • Sorbonne Center for Artificial Intelligence
Registration: Please apply on the event website • Application open until February 28, 2026
Organizer: Mannheim Institute for Intelligent Systems in Medicine • Sorbonne Center for Artificial Intelligence
ECTS: 2
This three-day workshop, taking place from the 24th to the 26th of June 2026, will bring together researchers working machine learning and related fields to exchange knowledge and explore advances in Artificial Intelligence for Medicine.
The event is will primarily be open to 4EU+ PhD students in medicine, biology, and computer science who wish to deepen their understanding of AI techniques and their applications in healthcare.
This event is jointly organised by the Sorbonne Cluster for artificial intelligence (SCAI) and Mannheim Institute for Intelligent Systems in Medicine (MIISM) and is financially supported by the international organisation “Franco-German University”.
4EU+ funding is paid prior to the trip. Accepted participants should contact angela.queisser@iwr.uni-heidelberg.de to start the funding process.
4EU+ funding per person: 369 € (79 € per night plus 211 € travel grant; top-up from your HGS MathComp travel budget is possible)
The event is will primarily be open to 4EU+ PhD students in medicine, biology, and computer science who wish to deepen their understanding of AI techniques and their applications in healthcare.
This event is jointly organised by the Sorbonne Cluster for artificial intelligence (SCAI) and Mannheim Institute for Intelligent Systems in Medicine (MIISM) and is financially supported by the international organisation “Franco-German University”.
4EU+ funding is paid prior to the trip. Accepted participants should contact angela.queisser@iwr.uni-heidelberg.de to start the funding process.
4EU+ funding per person: 369 € (79 € per night plus 211 € travel grant; top-up from your HGS MathComp travel budget is possible)
The aim of the three-day workshop offers young researchers a comprehensive, immersive learning experience. It kicks off on the first afternoon, following participants' midday arrival. The second day is intensive, alternating between expert lectures and hands-on sessions. The third day is dedicated to morning presentations before participants depart.
The multicultural environment encourages the comparison of scientific approaches and a deeper understanding of French and German research contexts. This dynamic is supported by the close collaboration between Sorbonne University and Heidelberg University in the fields of AI and health. The intercultural exchange, covering both scientific content and research practices, provides participants with significant added value for their training.
The program will feature a diverse range of formats, including plenary lectures to introduce the latest advancements in the field, concise presentations and poster sessions showcasing ongoing research, and practical workshops focusing on recent developments. Additionally, roundtable discussions will offer a platform for in-depth dialogue and idea exchange.
The multicultural environment encourages the comparison of scientific approaches and a deeper understanding of French and German research contexts. This dynamic is supported by the close collaboration between Sorbonne University and Heidelberg University in the fields of AI and health. The intercultural exchange, covering both scientific content and research practices, provides participants with significant added value for their training.
The program will feature a diverse range of formats, including plenary lectures to introduce the latest advancements in the field, concise presentations and poster sessions showcasing ongoing research, and practical workshops focusing on recent developments. Additionally, roundtable discussions will offer a platform for in-depth dialogue and idea exchange.
24.06.2026
16:30 - 18:00
16:30 - 18:00
Theory & Methods
"Machine learning galore!" Scientific Machine Learning
Colloquium
Location: Mathematikon • 5th Floor • Im Neuenheimer Feld 205 • 69120 Heidelberg
Registration: Please register via this form • Please register for free by 19 June 2026
Organizer: MLAI
Registration: Please register via this form • Please register for free by 19 June 2026
Organizer: MLAI
ECTS: 1 for 5
Machine learning galore will feature lab presentations by PIs as well as scientific talks by junior scientists.
To help plan the catering, please register for free by clicking here.
Scientific Machine Learning is a joint initiative from STRUCTURES and IWR aimed at fostering interactions within and development of the local machine learning community. Its portal summarizes the many relevant events and news from across campus that would otherwise remain scattered across single institutions or fields. The goals of the MLAI platform align with the STRUCTURES Cluster of Excellence's objective of driving research into the fundamental understanding of current and future machine learning, and with IWR’s aim to leverage machine learning to enable the solution of long-standing problems in the natural and life sciences, the engineering sciences, as well as the humanities.
Further information and links:
MLAI homepage • Machine Learning Talks on Campus – Information service and mailing list • STRUCTURES Cluster of Excellence
To help plan the catering, please register for free by clicking here.
Scientific Machine Learning is a joint initiative from STRUCTURES and IWR aimed at fostering interactions within and development of the local machine learning community. Its portal summarizes the many relevant events and news from across campus that would otherwise remain scattered across single institutions or fields. The goals of the MLAI platform align with the STRUCTURES Cluster of Excellence's objective of driving research into the fundamental understanding of current and future machine learning, and with IWR’s aim to leverage machine learning to enable the solution of long-standing problems in the natural and life sciences, the engineering sciences, as well as the humanities.
Further information and links:
MLAI homepage • Machine Learning Talks on Campus – Information service and mailing list • STRUCTURES Cluster of Excellence
Agentic AI
Christian Schulz
Daniel Schiller
Inga Ulusoy
Marc Ickler
Tobias Renkert
Vincent Heuveline
Case studies:
- Writing code faster
- Optimizing your code
- Hosting your own
- Injecting domain knowledge
- What does not work (yet)
For more see the abstract_file: Abstract-File
Christian Schulz
Daniel Schiller
Inga Ulusoy
Marc Ickler
Tobias Renkert
Vincent Heuveline
Case studies:
- Writing code faster
- Optimizing your code
- Hosting your own
- Injecting domain knowledge
- What does not work (yet)
For more see the abstract_file: Abstract-File
01.07.2026
- 02.07.2026
09:00 - 16:00
09:00 - 16:00
Key Competences
Thesis Defense Training
Compact Courses
Speaker: Dr. Jan Schmidt • janschmidt-training
Location: In-Person in Heidelberg
Registration: Please register on the course website
Organizer: Graduate Academy
Location: In-Person in Heidelberg
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.
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.
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.
It’s far more than “just” a presentation: defending your thesis is the last (and one of the biggest) challenges in your academic qualification – and it doesn’t only require well-prepared content. This workshop addresses aspects of the defense related to communication and presentation. We will work on participants’ body language as well as on strategies for convincing argumentative and rhetorical positioning during the disputation. A significant portion of the workshop will be devoted to simulated defenses and evaluations of the performances.