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
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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.
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finished (2023/05/31, finished 2023/11/17)
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