Position Description

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. HGS MathComp has 5 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:
(Please note additional or deviating information in the project listings below)

• Three-year contract
• Salary according to TV-L E13 level
• Faculty/department affiliation according to research group
• Start: 01 April 2024

Requirements:

• Above-average M.Sc. degree or equivalent (recognized in Germany)
• Excellent command of English
• Others as specified below

How to apply: see bottom of page!

PhD positions are available for the following PhD project topics and areas:

Data Science & Machine learning in the Life Sciences

• Research group: Biological Data Science
• PhD supervisor: Britta Velten
• Percentage of the position: 75%
• Start: 01 April 2024, or by mutual agreement
• Good level of expertise in programming, data analysis, statistics and/or machine learning, plus motivation for biological applications is required.
• Contact person for content questions: Britta Velten

Machine Learning and Astrophysics, Modelling dynamical systems with deep Operator Learning and NeuralODEs

• Research group: AstroAI-Lab
• PhD supervisor: Tobias Buck
• Contract duration: 3 years, extension for a further year possible
• Percentage of the position: 66-75%, depending on candidate profile
• Start: spring to fall 2024
• Prior knowledge in ML is needed, knowledge of dynamical systems, ODEs, PDEs, SDEs will be a plus. Good coding skills, both in python and C/C++ are required. Some astrophysics background would be beneficial but is not mandatory. Knowing JAX would be helpful.
• Contact person for content questions: Tobias Buck

Traction force microscopy for biological cells in three dimensions

• Research Group: Physics of Complex Biosystems
• PhD supervisor: Ulrich Schwarz
• Percentage of the position: 75%
• Start: open immediately
• A background in continuum mechanics, inverse problems and machine learning would be helpful. This project is funded by the excellence cluster 3DMM2O.
• Contact person for content questions: Ulrich Schwarz

Machine-learning approaches for modelling tumor cell plasticity and therapy resistance in brain tumors

• Research group: Biomedical Genomics Group @ IPMB
• PhD supervisor: Carl Herrmann
• Percentage of the position: 75%
• Start: April 2024 or later, to be discussed
• Strong experience in machine-learning/deep-learning is required. Knowledge in molecular/cellular biology would be a plus.
• Contact person for content questions: Carl Herrmann

Deep learning-based spectral image analysis enabled by synthetic data

• Research group: Division of Intelligent Medical Systems
• PhD supervisor: Lena Maier-Hein
• Percentage of the position: 100%
• Start: February 2024
• Advanced programming skills (Python), advanced math skills, experience in deep learning, good communication skills.
• Contact person for content questions: Lena Maier-Hein

Required documents (in ONE PDF file):

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

Deadline for applications: January 15, 2024

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

If you have any technical 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.