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.
28.04.2026
- 29.04.2026
09:00 - 17:00
09:00 - 17:00
Key Competences
Tailor Made Job Applications
Compact Courses
Speaker: Matthias Merkelbach • impulsplus
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.
Target group
This workshop has been designed for PhD candidates who want to prepare for the job search in a systematic way, or who want to learn more about application strategies and feel more confident in the application process.
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.
Target group
This workshop has been designed for PhD candidates who want to prepare for the job search in a systematic way, or who want to learn more about application strategies and feel more confident in the application process.
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.
Objectives
The workshop will provide participants with an overview over the different employment opportunities available for them. They will learn which strategies they can apply to find a job that matches their profile. Participants will also learn more about the career options that different occupational fields can offer.
Description
Participants will develop individual job application strategies based on their personal and professional background and employment options.
The relevant criteria that are obligatory for a written job application will be covered. Participants will also be given the opportunity to have their application documents analyzed and optimized, if desired.
The last part of the workshop will deal with the job interview. Which aspects should an interviewee pay special attention to, and what are the different elements of a typical job interview? Finally, participants will act out individual elements of a job interview to feel more confident in these situations.
Contents in brief
My job profile and employment options
Networking in a targeted way
Career prerequisites and application process
My individual application strategy
How to structure and present application documents in such a way that they appealto potential employers
Main aspects of a successful job interview
Methods
Brief presentations
Discussions in (small) groups
Peer advice
Resource oriented coaching exercises
The workshop will provide participants with an overview over the different employment opportunities available for them. They will learn which strategies they can apply to find a job that matches their profile. Participants will also learn more about the career options that different occupational fields can offer.
Description
Participants will develop individual job application strategies based on their personal and professional background and employment options.
The relevant criteria that are obligatory for a written job application will be covered. Participants will also be given the opportunity to have their application documents analyzed and optimized, if desired.
The last part of the workshop will deal with the job interview. Which aspects should an interviewee pay special attention to, and what are the different elements of a typical job interview? Finally, participants will act out individual elements of a job interview to feel more confident in these situations.
Contents in brief
My job profile and employment options
Networking in a targeted way
Career prerequisites and application process
My individual application strategy
How to structure and present application documents in such a way that they appealto potential employers
Main aspects of a successful job interview
Methods
Brief presentations
Discussions in (small) groups
Peer advice
Resource oriented coaching exercises
28.04.2026 ff
10:00 - 12:00
10:00 - 12:00
Key Competences
Data Management Plans in practice: From principles to action
Workshop
Speaker: Meriç Akdogan (Sorbonne University, France) • Laura Giovinazzi (University of Milan, Italy), Milan Janícek (Charles University, Czech Republic) • Carolina Manfredini (University of Milan, Italy)
Location: Online
Registration: Please register on the event website
Organizer: 4EU+ European University Alliance
Location: Online
Registration: Please register on the event website
Organizer: 4EU+ European University Alliance
ECTS: not yet determined
The movement for open science is transforming the academic world. In response, our 4EU+ training programme meets the growing demand for transparency, reproducibility, and collaboration by exploring a broad range of practices, such as open peer review, FAIR and open data, open software, and citizen science. In 2026, we invite you to explore the basics of open science in our introductory webinars followed by six specialized workshops between March and June.
These workshops are open to everyone and will be held online. They will focus on putting into practice what was covered in the webinars. Active participation in the exercises part is expected from those who register.
Two dates are scheduled for each workshop to encourage discussion within smaller groups. Please register for only one date per workshop:
- Tuesday, 28 April 2026, 10:00-12:00 AM
- Tuesday, 5 May 2026, 10:00-12:00 AM
Important: Please note that registration for the workshops will only open once the corresponding webinars have taken place.
ECTS subject to overall workload completed within the workshop series (please provide certificates after the program).
These workshops are open to everyone and will be held online. They will focus on putting into practice what was covered in the webinars. Active participation in the exercises part is expected from those who register.
Two dates are scheduled for each workshop to encourage discussion within smaller groups. Please register for only one date per workshop:
- Tuesday, 28 April 2026, 10:00-12:00 AM
- Tuesday, 5 May 2026, 10:00-12:00 AM
Important: Please note that registration for the workshops will only open once the corresponding webinars have taken place.
ECTS subject to overall workload completed within the workshop series (please provide certificates after the program).
A Data Management Plan (DMP) is a key research data management tool and a mandatory requirement for many funded projects. This hands-on workshop will allow the participants to analyse a partially completed DMP for a fictional research project and to contribute to the completion of key sections. To participate in this workshop, attendance at the webinar on open data is strongly recommended.
29.04.2026
16:30 - 18:00
16:30 - 18:00
Theory & Methods
"Machine learning galore!" Lab Presentation & Science Talks
Colloquium
Location: Mathematikon • 5th Floor • Im Neuenheimer Feld 205 • 69120 Heidelberg
Registration: Please register via this form • Please register for free by April 22nd, 2026
Organizer: MLAI
Registration: Please register via this form • Please register for free by April 22nd, 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
Lab presentations:
Sascha Diefenbacher • Lutz Greb • Christoph Schnörr
Rocket science:
Sascha Diefenbacher
Forecasting Generative Amplification
Andreas Albers (Greb lab)
Machine Learning for Molecular Property Prediction: Revisiting Empirical Chemistry with Big Data
Jonas Cassel (Schnörr lab)
Vector Bundle Data Models and Geometric Deep Learning
For more see the abstract_file: Abstract-File
Sascha Diefenbacher • Lutz Greb • Christoph Schnörr
Rocket science:
Sascha Diefenbacher
Forecasting Generative Amplification
Andreas Albers (Greb lab)
Machine Learning for Molecular Property Prediction: Revisiting Empirical Chemistry with Big Data
Jonas Cassel (Schnörr lab)
Vector Bundle Data Models and Geometric Deep Learning
For more see the abstract_file: Abstract-File