The European Research Council supports RWTH researchers in three lines of funding
The European Research Council (ERC) funds top-level researchers to pursue basic research and visionary projects. In recent months and weeks, RWTH researchers have again been considered with this prestigious grant in its three funding lines – the ERC Starting Grant for young researchers two to seven years after gaining their doctorate, the ERC Consolidator Grant for researchers seven to 12 years after completing their doctorate and the ERC Advanced Grant for outstanding, already established researchers.
ERC Advanced Grants
RWTH professors Martin Grohe and Heinz Pitsch have received funding from the European Research Council (ERC) in the form of Advanced Grants. Pitch is the first researcher at RWTH who has been awarded an Advanced Grant for the second time. Both professors will now be funded for five years by the ERC with some 2.5 million euros for their research and the associated equipment required.
As head of the Institute for Combustion Technology at RWTH, Heinz Pitsch is focused primarily on researching renewable energy sources in the field of thermochemical energy conversion. A particular role is played here by hydrogen-based fuels, since these do not produce exhaust gases harmful to the climate and are good for both storage and transport of the energy produced from solar and wind-powered sources. Combustion offers major advantages for the use of hydrogen for energy purposes, but it simultaneously gives rise to challenges that the HYDROGENATE research project aims to examine, understand and put to use. This research represents an important contribution to the energy transition.
The research topics pursued by Professor Martin Grohe relate to algorithms and complexity, logic, database theory, graph theory and machine learning. The aim of his ERC project is to develop a comprehensive theory of graph similarity and to develop its applicability for practically relevant problems. Graphs are versatile models that represent complex data, from that of chemical molecules up to that of social interactions. In analyzing graph-based data, a fundamental task is to compare graphs and to measure their similarity in a semantically meaningful and algorithmically efficient manner. A central problem here is what is known as the graph isomorphism problem. This calls for an efficient algorithm that decides whether two graphs are structurally identical.
ERC Consolidated Grants
At an earlier stage in their work are Professor Laura De Laporte and Professor Rafael Kramann, who have been awarded Consolidator Grants. Consolidator Grants provide funding for scholars when they are consolidating their own research team or program, according to the ERC. To be eligible for funding, scholars must demonstrate the pioneering features, ambition, and feasibility of their proposal.
Chemist Laura De Laporte is a professor at the Advanced Materials for Biomedicine Teaching and Research Area at RWTH, Uniklinik RWTH Aachen, and DWI-Leibniz Institute for Interactive Materials. With her HEARTBEAT research project, De Laporte and her team aim to break with conventional methods of manufacturing 3D biomaterials by assembling and crosslinking a variety of unique preprogrammed, rodshaped, and interactive microgels instead of molecular building blocks. The goal is to achieve macroporous, aligned, activatable and, if needed, degradable constructs after automatic mixing of different microgels and stem cells, which is not possible with conventional hydrogels. In HEARTBEAT, De Laporte focuses on using bottom-up interactive microgel assemblies to generate vascularized pieces of beating heart tissue at a millimeter scale.
Professor Rafael Kramann is head of the Institute of Experimental Internal Medicine and Systems Biology at RWTH and senior physician at the Clinic for Renal and Hypertensive Diseases, Rheumatological and Immunological Diseases at Uniklinik RWTH Aachen. The aim of the TargetCKD project is to use state-of-the-art methods to decode kidney diseases and develop both diagnostic and new treatment approaches. Chronic kidney failure affects over ten percent of the population in Europe, yet there are currently no reliable biomarkers that can predict disease progression or non-invasively diagnose specific kidney diseases. In addition, there are no suitable treatment options. (Kramann Laboratory).
ERC Starting Grants
To qualify for ERC Starting Grants, applicants must demonstrate outstanding preliminary investigations and must submit the application no later than seven years after completion of their doctorate. Professor Michael Schaub, junior professor for computational network science in the Department of Computer Science, Dr. Christoph Kuppe, research group leader at the Institute of Experimental Internal Medicine and Systems Biology, and Dr. Yang Shi, research group leader at the Institute for Experimental Molecular Imaging, were successful with their applications and will now each receive up to 1.5 million euros for their continued research.
Complex networks are omnipresent in our world. From both theoretical and practical perspectives, much of Professor Michael Schaub’s research investigates the interplay between structure and dynamic processes that take place in a network. To this end, his research group combines data- and model-based methods from fields such as machine learning and dynamical systems theory. Schaub’s successful proposal ‘HIGH-HOPeS – Higher-Order Hodge Laplacians for Processing of Multiway Signals’ aims to develop efficient methods to better understand relations between multiple nodes.
Kidney disease, especially when caused by diabetes mellitus, also known as diabetic nephropathy, is a growing problem for healthcare systems worldwide. In the project ‘Decoding Diabetic Kidney Disease – DECODE-DKD’, Dr. Christoph Kuppe and his team are investigating new pathophysiological principles to better understand the disease mechanisms of diabetic nephropathy. The aim is to use new patient-centered methods to develop new therapies. In a first step, a ‘map’ of regulatory gene changes will be generated for each cell of the kidney to gain a better understanding of pathophysiological changes. In addition, these data will be used to better predict a patient’s disease course.
Immunotherapy has significantly advanced the treatment of cancer. However, cancer can only be fully cured in a fraction of patients. Since 2016, Dr. Yang Shi and his research group have focused on developing polymeric therapeutic systems to make cancer immunotherapy more effective for more people with the disease. With the BeaT-IT project, funded by the Starting Grant, Yang’s group will use novel polymer biomaterials from the nanoscale to the macroscale to enhance cancer immunotherapy. The project aims to gain a better understanding of how B cells – which are responsible for the formation of antibodies, can be modulated and used in cancer immunotherapy.
– Thorsten Karbach