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.
06.10.2026
17:15
17:15
Theory & Methods
Lieseberg Colloquium: Extending Low-cost Electronic Structure Methods for Automated in silico Chemistry
Colloquium
Speaker: Dr. Philipp Pracht • IWR, Heidelberg University
Location: Hörsaal West • Im Neuenheimer Feld 252, 69120 Heidelberg
Organizer: Institute of Organic Chemistry
Location: Hörsaal West • Im Neuenheimer Feld 252, 69120 Heidelberg
Organizer: Institute of Organic Chemistry
ECTS: not yet determined
Im Rahmen der Lieseberg-Kolloquien werden Vorträge von Wissenschaftlern/innen aus allen Bereichen der chemischen Forschung gehalten. Die Vorträge finden während des Semesters in der Regel dienstags um 17:15 Uhr im Hörsaal West INF 252 statt (Abweichungen sind in dem Veranstaltungsprogramm vermerkt); ab 17:00 Uhr wird Kaffee und Gebäck serviert. Die Lieseberg-Kolloquien werden von Dr. Tobias Morack koordiniert.
Which structures a molecule adopts, how stable they are, and how they show up in a spectrum
are all governed by the potential energy surface. Exploring it requires many thousands of
energy and force evaluations per molecule, far more than density functional theory can afford
for systems of realistic size. Semiempirical methods such as tight-binding retain the essential
quantum mechanics at a fraction of the cost, and the automated programs build on them to
sample ensembles and derive thermodynamic and spectroscopic properties automatically.
This talk introduces these methods and workflows and then presents four recent extensions:
a divide-and-conquer scheme that takes xTB to thousands of atoms, analytic second
derivatives for IR and Raman spectra, a graph-based sampling strategy for flexible side chains,
and a permutation-invariant structure comparison. Together they point towards the automated
identification of unknown compounds from measured spectra.
are all governed by the potential energy surface. Exploring it requires many thousands of
energy and force evaluations per molecule, far more than density functional theory can afford
for systems of realistic size. Semiempirical methods such as tight-binding retain the essential
quantum mechanics at a fraction of the cost, and the automated programs build on them to
sample ensembles and derive thermodynamic and spectroscopic properties automatically.
This talk introduces these methods and workflows and then presents four recent extensions:
a divide-and-conquer scheme that takes xTB to thousands of atoms, analytic second
derivatives for IR and Raman spectra, a graph-based sampling strategy for flexible side chains,
and a permutation-invariant structure comparison. Together they point towards the automated
identification of unknown compounds from measured spectra.
08.10.2026
09:00 - 17:00
09:00 - 17:00
Key Competences
Time and Project Management
Compact Courses
Speaker: Dr. Jan Stamm • impulsplus
Location: Online
Registration: Please register on the course website
Organizer: Graduate Academy
Location: Online
Registration: Please register on the course website
Organizer: Graduate Academy
ECTS: 0.5
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.
This workshop provides you with basic strategies and tools for an effective and efficient time and project-management. You will get specific ideas for improving your own approach towards organizing yourself and your work. The motto of the workshop is: Becoming a better, smarter, more focused time-manager is an evolution not a revolution. You already have a lot of the ideas and skills that you need. This workshop helps you to understand them in a deeper way and to commit yourself to really using them.
Contents in brief:
Successful project management (milestone plans vs. iterative incremental approach), basic strategies and tools for an efficient time and self-management (i.e. Pomodoro Technique, phases of productivity, implementation intentions), setting priorities, pragmatism and productivity).
Methods:
Input and discussion, individual and group work, coaching techniques.
Contents in brief:
Successful project management (milestone plans vs. iterative incremental approach), basic strategies and tools for an efficient time and self-management (i.e. Pomodoro Technique, phases of productivity, implementation intentions), setting priorities, pragmatism and productivity).
Methods:
Input and discussion, individual and group work, coaching techniques.
12.10.2026
- 13.10.2026
09:30 - 18:00
09:30 - 18:00
Theory & Methods
Modern Shape-Constrained and Nonparametric Statistical Learning: Theory, Methods, and Applications
Compact Courses
Speaker: Prof. Richard Samworth • University of Cambridge
Location: Karlsruhe Institute of Technology
Registration: Please register on the event website • Registration open until 13 September 2026
Organizer: STAT & MathSEE/KCDS, KIT • HGS MathComp, Heidelberg University
Location: Karlsruhe Institute of Technology
Registration: Please register on the event website • Registration open until 13 September 2026
Organizer: STAT & MathSEE/KCDS, KIT • HGS MathComp, Heidelberg University
ECTS: 1
The workshop is primarily intended for doctoral candidates and postdoctoral researchers from the KCDS Graduate School and the Heidelberg Graduate School MathComp, as well as members of the Helmholtz Association and researchers in related fields who have a strong interest in modern mathematical statistics.
Participants will gain insight into current developments in adaptive statistical methodology and their connections to broader challenges in statistical learning and modern data analysis.
The workshop and keynote lecture are organised by the Institute of Statistics (STAT) in cooperation with MathSEE / KCDS and HGS MathComp at Heidelberg University. We thank MathSEE/KCDS, HGS MathComp and HGF HIDA (Course Funding) for their generous support.
Participants will gain insight into current developments in adaptive statistical methodology and their connections to broader challenges in statistical learning and modern data analysis.
The workshop and keynote lecture are organised by the Institute of Statistics (STAT) in cooperation with MathSEE / KCDS and HGS MathComp at Heidelberg University. We thank MathSEE/KCDS, HGS MathComp and HGF HIDA (Course Funding) for their generous support.
Workshop:
Building on familiar classical methods such as linear regression, the workshop will guide participants towards recent ideas in distributional adaptivity and explore their relevance to statistical learning and modern data analysis. Participants with a good understanding of classical statistical methods and an interest in mathematical statistics are warmly encouraged to join.
Keynote "Outrigger Local Polynomial Regression":
Date & Time: 13 October 2026, 16:30
Venue: NTI Lecture Hall, KIT Campus South
The talk will revisit the classical method of local polynomial regression from a modern perspective, showing how it can be adapted to the diverse error distributions encountered in contemporary applications. Along the way, it will introduce the main methodological ideas and explore the mathematical theory underlying the new approach.
Building on familiar classical methods such as linear regression, the workshop will guide participants towards recent ideas in distributional adaptivity and explore their relevance to statistical learning and modern data analysis. Participants with a good understanding of classical statistical methods and an interest in mathematical statistics are warmly encouraged to join.
Keynote "Outrigger Local Polynomial Regression":
Date & Time: 13 October 2026, 16:30
Venue: NTI Lecture Hall, KIT Campus South
The talk will revisit the classical method of local polynomial regression from a modern perspective, showing how it can be adapted to the diverse error distributions encountered in contemporary applications. Along the way, it will introduce the main methodological ideas and explore the mathematical theory underlying the new approach.