Heidelberg University, Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences (HGS MathComp)

Position ID: HGSMathComp-PHD [#22517]
Position Title: 18 Interdisciplinary PhD Positions (f/m/d)
Position Location: Heidelberg, Baden-Wuerttemberg 69120, Germany [map] sort by distance
Subject Areas: Mathematics, Computer Science, Physics, Biology, Chemistry, and Life Sciences
Salary Range: Agreement of tariffs: TV-L E13 level
Application Deadline: 2023/07/15 11:59PMhelp popup (posted 2023/05/31)
Position Description:    

*** the listing date or deadline for this position has passed. ***

18 Interdisciplinary PhD Positions (f/m/d) at Heidelberg University


The Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences (HGS MathComp) at Heidelberg University is the leading graduate school in Germany that focuses on the complex topic of Scientific Computing. Located in a vibrant research environment, the school offers a uniquely structured interdisciplinary education for PhD students. HGS MathComp has 18 open PhD positions in the general research areas of Mathematics, Computer Science, Physics, Biology, Chemistry, and Life Sciences.

Scope and duration of the PhD positions:

  • Three-year contract with the possibility of extension; salary according to TV-L E13 level; contract details depend on research project
  • Faculty/department affiliation according to research group
  • Start: October 1, 2023, unless otherwise stated below
  • Application details: see bottom of page

PhD positions are available for the following PhD project topics:

Immersed interface methods for the simulation of cell movement


Multiscale Methods and Localised Model Reduction for Convection-Dominated Problems and Applications in Climate Modelling


Modeling and simulation of thermochemical energy conversion processes for the flexible use of hydrogen-based renewable fuels


Transformer-based cell tracking in virology

  • Research group: Image Analysis and Learning
  • Supervisor: Prof. Dr. Fred Hamprecht
  • Start: Position available immediately
  • Additional Information: The aim is to develop software that biologists will really be able to use. The project entails a large software component, and the ideal candidate brings experience in full stack software development, a deep understanding of machine learning, and a passion to help address some of humanity's greatest challenges by working closely with virologists from SFB 1129. We are a small and friendly team that has previously made real contributions to the bioimage analysis community (ilastik, plantseg)


Geometric machine learning in quantum chemistry: learning kinetic energy density functionals

  • Research group: Image Analysis and Learning
  • Supervisor: Prof. Dr. Fred Hamprecht
  • Start: Position available immediately
  • Additional information: If successful, this project will enable a breakthrough in the computational cost of quantum chemical calculations. A solid understanding of quantum mechanics and machine learning are required. We are a small and friendly team and work on this exciting project together with the lab of Prof. Dr. Andreas Dreuw in the simplaix consortium.


Modelling cytoadhesion of malaria-infected red blood cells


Traction force microscopy for biological cells in three dimensions


Domain Uncertainty Quantification

  • Research group: UQ and Scientific Machine Learning
  • Supervisor: Jun. Prof. Dr. Jakob Zech
  • Additional information: Applicants should possess a strong background in mathematics, ideally with a focus on PDEs. Experience with machine learning is also highly beneficial. Postdocs are welcome.


Machine Learning for Programming (2 PhD positions)

  • Research group: Parallel and Distributed Systems (PVS)
  • Supervisor: Prof. Dr. Artur Andrzejak
  • Start: September 1 or October 1, 2023 for one position, later start possible for second position
  • Additional information: Research fields are ML/AI-based approaches for code-to-code translation, vulnerability detection, performance optimization, and AI-assisted programming. Background and experience in deep learning for NLP and/or source code analysis are a plus. Postdocs are welcome. Very good command of the German language is a requirement for at least one of these positions.


Model based AI: Physics Informed Neural Networks (fundamental research)

  • Research group: Data Analysis and Modeling in Medicine
  • Supervisor: Prof. Dr. Jürgen Hesser
  • Additional information: Background in mathematics with experience in machine learning and PDEs or computer science with good background in machine learning (ideally physics informed neural networks) but also with a good math background


Machine Learning and Model-based controller (applied research)


Biomedical Modeling with PDEs and Machine Learning (applied research) (2 PhD positions)


Magnetic Resonance Imaging: AI based patient-specific MRI acquisition optimization


Magnetic Resonance Imaging: Sequence development for a local breast gradient coil


New numerical schemes and parallel algorithms in scientific computing (2 PhD positions)

Required documents:

  • CV
  • Letter of motivation
  • Most recent or final transcript of records
  • Names and contact information of three references

All documents must be uploaded as one PDF via our application portal.

Deadline for applications: July 15, 2023

There will be interviews between the group leaders and potential candidates to discuss the specifics of the respective positions.

If you have any questions, please contact hgs@iwr.uni-heidelberg.de. Please note that applications will only be accepted via the application portal, not via email.

Heidelberg University stands for equal opportunities and diversity. Qualified female candidates are especially invited to apply. Persons with severe disabilities will be given preference if they are equally qualified. Information on job advertisements and the collection of personal data is available at www.uni-heidelberg.de/en/job-market.

We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://joanna.iwr.uni-heidelberg.de/Portfolio_HGS/FGEN/form/fgen_form.php?id_form=69 external link.
Contact: Angela Queisser
Email: email address
Postal Mail:
HGS MathComp
Im Neuenheimer Feld 205
Room 5/214
69120 Heidelberg
Web Page: https://adb.zuv.uni-heidelberg.de/info/INFO_FDB$.startup?MODUL=LS&M1=1&M2=0&M3=0&PRO=33376