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The Cluster of Excellence "Data-Integrated Simulation Science" (EXC 2075) is an interdisciplinary research center with more than 200 scientists of different ages, gender identities, nationalities and different subject areas, jointly performing research towards a common goal: We target a new class of modeling and computational methods based on available data from various sources, in order to take the usability, precision and reliability of simulations to a new level.
The project/The position:
We are looking for a motivated and creative PhD candidate who will pursue research in the area of magnetic gels, using various simulation approaches as well as machine learning and uncertainty quantification techniques. Magnetic Gels are smart materials whose shape and elasticity can be controlled by magnetic fields. It is expected that they may be useful in biomedical applications, such as drug delivery as well as actuation on the nano- and mesoscale. You will be afiliated at the Institute for Computational Physics, University of Stuttgart, and be part of the graduate school of the Cluster of Excellence SimTech for Data-integrated simulation science.
- Develop, run, and study simulation models for magnetic gels, capturing the complexity of the microstructure found in experiments. The methods being used include coarse-grained molecular dynamics and lattice-Boltzmann hydrodynamics.
- Create datasets linking microscopic and macroscopic properties of the materials.
- Using machine learning techniques and uncertainty quantification, shed light on which aspects of the microstructure can be used to tailor the material properties for applications.
- Closely cooperate and exchange knowledge and ideas with other scientists, in particular from experimental disciplines.
- Perform necessary improvements of the scalability of the simulation code (http://espressomd.org), potentially using task-based parallelism.
- Publish research results and present them at conferences.
- Good degree in physics or a related discipline or alternatively a degree in computer science and proven qualifications in physics.
- Ideally, previous experience in scientific computing, data science, or simulations. Experience in particle-based simulations and/or lattice-Boltzmann is an asset.
- Previous experience in soft matter or statistical physics is an asset.
- The curiosity and determination to pursue an interesting and complex research
- A strong interest to interact and collaborate with other scientists, including from other disciplines than your own.
- Experience in an object-oriented programming language such as Java or C++. Skills in C++ are an asset.
- Excellent verbal communication skills in English or German, proficiency in written English is an asset.
- An inspirational and supportive research environment at the Institute for Computational Physics and the Cluster of Excellence SimTech with ample networking
- A nationally and internationally well-connected research group.
- Fully funded conference visits and a fully funded research stay abroad.
- Access to excellent compute resources.
- Training programs by the graduate school and the High Performance Computing Center Stuttgart to support your first steps as an early career scientist.
Please submit your application, including one-page motivation letter, academic CV, contact information for two references, as well as academic certificates and transcript of records, via email@example.com. If you have any questions regarding this application, please contact me via firstname.lastname@example.org.
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At the University of Stuttgart and the Cluster of Excellence EXC 2075, we actively promote diversity among our employees. We have set ourselves the goal of recruiting more women scientists and employing more people with an international background, as well as people with disabilities. We are therefore particularly pleased to receive applications from such people. Regardless, we welcome any good application.
Women who apply will be given preferential consideration in areas in which they are underrepresented, provided they have the same aptitude, qualifications and professional performance. Severely disabled applicants with equal qualifications will be given priority.
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