Several Interdisciplinary PhD Positions bei Universität Heidelberg

Several Interdisciplinary PhD Positions (f/m/d) bei Universität Heidelberg

Universität Heidelberg

Several 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 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

Your tasks include:

Successful completion of your dissertation
Involvement in high-quality research, with the aim of publication in international journals and at international conferences
Involvement in the organization of academic events, such as talks, workshops/conferences, and summer schools
Teaching and supervision of Bachelor’s and Master’s students
Participation in HGS MathComp training and networking activities

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):