Dual Career

The project is embedded in a larger collaboration with MPI-CBG and TUD’s Department of Mathematics and aims to exploit recent advances in numerical integration given by the generalization of the classic Gauss quadrature rules to arbitrary dimensions. Based on these results, new algorithms for computing surface integrals or more general integrals on high dimensional manifolds shall be developed. The core ingredient of the approach is given by novel solutions of high-dimensional interpolation problems with vastly improved computational performance and accuracy.

Integration and interpolation are at the heart of many applications in scientific computing, from numerical solutions of differential equations, to deep learning.

You will work with experts in the field of mathematics to further develop the algorithmic foundations, and with colleagues from the other CASUS Departments in order to apply the new algorithms.

Applications include, but are not limited to, computing total energies of deforming synthetic materials or total concentrations for polar gel models of biological tissue dynamics.

Job Offer [PDF, 187 KB]

The project is embedded in a larger collaboration with MPI-CBG and TUD’s Department of Mathematics and aims to exploit recent advances in high-dimensional interpolation problems with vastly improved computational performance and accuracy.

Interpolation is at the heart of many applications in scientific computing. In particular, it allows to derive polynomial level set parametrizations of non-flat manifolds. This fact shall be incorporated into the development of novel numerical solvers of PDE’s on curved surfaces and complex shapes.

You will work with experts in the field of mathematics to further develop the algorithmic foundations, and with colleagues from the other CASUS Departments in order to apply the new algorithms.

Applications include, but are not limited to, discretizing active polar gel models of biological tissue dynamics and simulating deformations of synthetic materials.

Job Offer [PDF, 186 KB]

The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. We combine innovative methods from mathematics, theoretical systems research, simulations, data science, and computer science to provide solutions for a range of disciplines – materials science under ambient and extreme conditions, earth system research, systems biology, and autonomous vehicles.

CASUS was jointly founded in August 2019 by the Helmholtz-Zentrum Dresden-Rossendorf, the Helmholtz Centre for Environmental Research, the Max Planck Institute of Molecular Cell Biology and Genetics, the Technical University of Dresden and the University of Wroclaw. CASUS is located in the heart of Görlitz at the border between Germany and Poland. The CASUS start-up phase is hosted by the Helmholtz-Zentrum Dresden-Rossendorf and is financed by the Federal Ministry of Education and Research and the Saxon State Ministry of Science and Art.

The Department of Systems Biology in collaboration with the Junior Professorship for Immersive Media at TU Dresden is looking for a PhD student excited about exploring the possibilities of combining natural user interfaces (e.g. via eye tracking) with machine learning-based approaches for interactive data analysis in Systems Biology. Consideration of candidates will begin as soon as possible and will continue until the position is filled. Location of work is Görlitz, remuneration is according to the German Civil Service Tariff and HZDR employment conditions. No tuition charged. The regular weekly working time will be 19,5 hours and will be increased to 30 hours in the third working year.

Link: https://www.hzdr.de/db/Cms?pNid=490&pOid=61905&pContLang=en

In recent years, amazing new scientific instruments have been developed. These include Lightsheet Fluorescence Microscopes or sample manipulators based on FLUCS, offering unprecedented insight into biological systems live and in 3D. In parallel, AR/VR/XR interfaces have moved out of the lab and have become widely available, while solving many of the issues earlier setups had, such as motion sickness or limited resolution. So far, both have not been paired yet, and essentially all of these instruments are still controlled using traditional mouse/keyboard input and 2D screens! Our goal in this project is to bring together state-of-the-art scientific instruments in Systems Biology with AR/VR/XR visualization and control modalities, both for single-user and for multi-user environments.

Link: https://www.hzdr.de/db/Cms?pNid=490&pOid=61903&pContLang=en

CASUS's Systems Biology Department, in partnership with the Center for Systems Biology Dresden and the Federal Cluster of Excellence “Physics of Life” at TU Dresden, seek to understand living matter on the basis of physical principles.

A physical principle that has been particularly successful in describing the behavior of active biological material out of equilibrium is the theory of Active Polar Gels. Traditionally, this theory is used in a top-down way starting from the conservation laws expressed as partial differential equations. While this was successful, it begs the question what the values and molecular meanings of the coefficients in the equations are.

In this project, we address this fundamental question in a data-driven way. We exploit recent advances in learning mathematical models from data (https://arxiv.org/abs/1907.07810) in order to use microscopy videos of developing embryos to learn bottom-up physical models. These data-driven model will include the chemical regulation and the biomechanics of the tissue in an attempt to explain the self-organized emergence of shape and function during morphogenesis. Comparing these models with the top-down derived models will provide new insight into the mysterious physics of life.

Job Offer [PDF, 196 KB]

You are expected to apply high-fidelity electronic structure methods (DFT-MD and TDDFT) to compute electronic transport properties (dynamical structure factor, electrical conductivity, and stopping power) in warm dense matter.

You will devise a theoretical formalism and develop modeling techniques to capture the physics in high-fidelity data from TDDFT within a surrogate model for the numerical modeling of warm dense matter that is computationally more efficient.

You will implement the surrogate model in a suitable software package and validate it against high-fidelity data.

You will also complement state-of-the-art fluid dynamics and magneto-hydrodynamics codes with on-the-fly data from high-fidelity simulations and your surrogate model.

In collaboration with our partners at international research institutions and the Helmholtz association, your surrogate model will support the successful characterization of HED phenomena generated in laboratories such as coherent light sources and pulsed power facilities.

Job Offer [PDF, 152 KB]