
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...]
09:00 - 15:00
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Location: Online
Registration: Please register on the event website
Organizer: Graduate Academy
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.
In the theoretical part of the training, you will learn techniques for structuring complex information logically and for designing easy-to-understand slides and stories. In the practical part, you will then apply these techniques to your very own research findings and produce your own presentation. By the end of the training, you will have a coherent storyline of your own academic presentation as well as drafts of most of your slides.
Important:
This training focuses on the logic of good presentations; it does not cover the use of presentation software like PowerPoint.
Receive individual feedback:
Prior to the training, you can send an already existing presentation to the trainer at markus.burger@slidewriting.com and receive individual feedback.
09:00 - 14:00
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Location: Mathematikon • Seminar Room 10, 5th floor • Im Neuenheimer Feld 205, 69120 Heidelberg
Registration: Please register here • Registration open until February 17, 2025
Organizer: HGS MathComp
In several fields of research as diverse as medicine, biology and finance, one seeks to understand the dynamics of a complex system from a multivariate time series. The aim of this course is to give an overview on some recent advances in the modelling of multivariate time series.
The course will be 3 hours per day (in the morning) over 5 days and a one hour exercise/practical session each afternoon.
Feb 20, 21, 24, 25, 26
9:00-12:00 and 13:00-14:00
Prerequisites: basic knowledge in statistics, linear algebra and functional analysis (equivalent to 1-2 semesters bachelor studies) is expected.
1. Notions of stationarity.
2. Vector Autoregressive models and estimation.
3. Spectral density matrices and estimation.
4. Overview of sampling properties of the estimators.
Part 2: Covariance and Matrices
1. Projections, linear regression and partial correlation.
2. Connection between partial correlation and the inverse covariance matrix.
3. The Schur complement for finite and infinite dimensional matrices.
4. Some properties of the inverse of infinite dimensional matrices.
Part 3: Gaussian Graphical models in time series
1. Gaussian graphical models for VAR models.
2. Gaussian graphical models for general time series and its connection to infinite dimensional matrices.
3. Gaussian graphical models for stationary time series and spectral analysis.
4. Estimation of graphical models for both low dimension and high dimensional time series.
Part 4: Graphical models for non-Gaussian time series
1. The exponential family of distributions.
2. The connection between the exponential family and graphical models.
3. Conditionally specified distributions for graphical modelling of multivariate time series.
09:30 - 16:15
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Location: Online
Registration: Please register on the event website
Organizer: Graduate Academy
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.
Please note: Your tutor expects you to participate actively in the interactive workshop. You should be willing to turn on your camera.
Contents:
- Definitions of good scientific practice and scientific misconduct
- Degrees and extent of scientific misconduct
- Examples for responsible and irresponsible conduct of research
- Data management
- Authorship and the process of publication
- Mentoring and supervision
- Conflict management: how to deal with scientific misconduct
- Reactions to scientific misconduct
- Local, national and international guidelines and regulations