Heidelberg Graduate School of Mathematical and Computational Methods

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.

Ihre Aufgaben

• 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.

Ihr Profil

• Above-average M.Sc. degree or equivalent (recognized in Germany)

• Excellent command of English

• Others as specified below,

• Advanced programming skills (Python), advanced math skills, experience in deep learning, good communication skills.

Wir bieten Ihnen

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

Kontakt

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., Application webpage: https://forms.office.com/e/xhDPAWwDif