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Simulierte Rauchwolken
Mit den Algorithmen von Prof. Thürey lassen sich solche Wolken simulieren. Sein Projekt DataFlow wird mit einem Proof of Concept Grant gefördert. (Bild: Xie, Franz, Chu, Thuerey / TUM)
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ERC Advanced and Proof of Concept Grants awarded to TUM researchers

Cutting-edge research from robotics to simulated flows

The European Research Council (ERC) will fund three projects by scientists from the Technical University of Munich (TUM) through prestigious Advanced Grants. Two of the projects deal with new approaches to cancer treatment. The third will investigate how walking robots can become more effective. Furthermore, a project on the simulation of flows will be funded through a Proof of Concept Grant.

Each year, the European Research Council awards grants in various categories. The Advanced Grants are reserved for excellent established scientists who can point to outstanding accomplishments in the past decade. The grants provide funding of up to 2.5 million euros.

In addition to the three Advanced Grants, the ERC is sponsoring another project through a Proof of Concept Grant. These grants are awarded to scientists who wish to determine whether their ERC research projects are likely to lead to marketable innovations. As an entrepreneurial university, TUM attaches great importance to this aspect of research and specifically promotes start-up companies founded by researchers and students.

Prof. Dr. Alin Albu-Schäffer (Informatics)

In the near future, robots are supposed to move around like their biological models: humans and animals. In the “M-Runners” project, Prof. Albu-Schäffer will therefore refine the mobility and efficiency of two- and four-legged robots. The locomotion of humans and animals is determined by bio-mechanical resonance properties of the body. Understanding this mechanism is a basic requirement for achieving a scientific breakthrough in robotic walking. To make robot movements less susceptible to failure and more energy efficient, a robotic body must be designed to be consistent with periodic motions. This requires, among other things, mathematical methods to describe, analyze, design and control systems whose resonance is nonlinear. Such methods have yet to be devised. In his new project, Prof. Albu-Schäffer aims to develop a new theory of nonlinear oscillations, which should then be applied to elastic systems − both robotic and biological.

Alin Albu-Schäffer is Professor of Sensor Based Robotic Systems and Intelligent Assistance Systems. Since 2012 he has also been Director of the Institute of Robotics and Mechatronics at the German Aerospace Center (DLR).

Prof. Dr. Bernhard Küster (TUM School of Life Sciences)

As in the rest of the body, processes that occur in cancer cells are controlled by proteins. The activity of those proteins, in turn, is regulated to a significant degree by kinases. These molecules serve as the starting point for a class of cancer drugs. Some forms of cancer are characterized by altered protein activity. By inhibiting kinases, such drugs can affect the course of the disease. In his “TOPAS” project, Prof. Bernhard Küster plans to measure protein activity in cancer cells with the help of quantitative mass spectrometry. It is expected that the tumor proteome activity status, or TOPAS for short, will provide additional information about the specific cancer in question. Another aim of the project is to use TOPAS to determine which kinase inhibitors are particularly promising targets for the treatment of a patient. Küster and his team also want to show that a so-called TOPAS score can provide physicians with important additional information in clinical practice.

Bernhard Küster is Professor of Proteomics and Bioanalytics.

Prof. Dr. Jürgen Ruland (Medicine)

T-cell non-Hodgkin's lymphomas (T-NHLs) are a particularly aggressive form of lymph node cancer that respond poorly to conventional therapies. Normally, T cells protect the body from threats, including cancer. However, in this disease entity the cells mutate and begin to reproduce uncontrollably. In his “T-NHL SUPPRESSORS” project, Prof. Jürgen Ruland plans to study the molecular mechanisms that make T-NHLs so dangerous and to explore potential countermeasures. The point of departure is the PD-1 protein, a kind of emergency stop switch for defective cells discovered by Ruland and his team in 2017. In nearly a third of T-NHL patients, this switch is dysfunctional and therefore unable to prevent mutated cells from proliferating. The researchers’ aims are to determine how PD-1 prevents lymphomas from growing and to explore other molecular processes that can limit the growth of T-NHLs.

Jürgen Ruland is Professor of Clinical Chemistry and Pathobiochemistry. His research previously received funding through an ERC Advanced Grant in 2013.

Proof of Concept Grant: Prof. Dr. Nils Thürey (Informatics)

Computer simulations of flows can be useful in many areas − whether in the design of modern pipelines or in automotive development. Such simulations can be used, for example, to calculate air streams around vehicles or blood flow in human veins without having to perform expensive real-life experiments. Flow simulations are now routine in many industries. However, it can still take several days to perform the required calculations. Prof. Nils Thürey is working on methods to improve such simulations. The Proof of Concept Grant for his project, entitled “dataFlow: a Data-driven Fluid Flow Solving Platform”, will help to refine a deep-learning algorithm that was the outcome of Prof. Thürey’s earlier ERC Starting Grant project “realFlow”. The algorithm could make it possible to perform flow simulations on normal desktop PCs within just a few seconds. In this method, neural networks are trained to recognize recurring patterns in simulations. Once those patterns have been saved to memory, the data-driven model is able to generate new results much faster.

Nils Thürey is Professor of Physics-based Simulation.

More Information:

ERC grants at TUM

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Technical University of Munich Paul Hellmich
paul.hellmich(at)tum.de

Article at tum.de

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