• 4/26/2022
  • Reading time 3 min.

Medicine. Astrophysics. Machine Learning: TUM researchers awarded ERC Advanced Grants

Three cutting-edge research projects to receive EU funding

Treating the causes of diabetes, building a deep-sea telescope to find cosmic particles, and using machine learning to predict the effects of drugs on cells - these are the goals of three projects by researchers at the Technical University of Munich (TUM), which will supported in the future with the European Research Council's highly-endowed ERC Advanced Grants.

Prof. Dr. Elisa Reconi Juli Eberle / TUM
Elisa Resconi, Liesel Beckmann Professor for Experimental Physics with Cosmic Particles at TUM, receives an ERC Advanced Grant for the NEUTRINOSHOT project. In it, an underwater observatory for cosmic particles will be built off the coast of Canada.

Researchers at TUM have received a total of 157 prestigious ERC Grants to date. The ERC awards grants in various categories every year. Advanced Grants, which are set aside for established, leading scientists with a track record of significant research achievements over the past 10 years, come with up to 2.5 million euros in funding.

Prof. Dr. Heiko Lickert (Medicine)

Currently no drug treatment can stop the progression of diabetes, a disease characterized by loss or dysfunction of insulin-producing beta cells in the pancreas. With his ERC-funded project “BetaRegeneration”, Heiko Lickert will decipher cellular and molecular mechanisms of beta cell protection and regeneration. Based on the previous identification and validation of known and novel therapeutic targets and combinatorial pharmacology, new avenues of targeted and combinatorial beta cell protection and regeneration are explored. If successful, BetaRegeneration will initiate a paradigm shift from symptomatic to causal diabetes therapy.

Heiko Lickert is Professor of Beta-Cell Biology at TUM and Director of the Insitute for Diabetes and Regeneration Research at Helmholtz Munich. Among other scientific awards, he received an ERC Starting Grant in 2010.

Prof. Dr. Elisa Resconi (Physics)

Cosmic neutrinos testify to the massive processes at the verges of supermassive black holes and other phenomena. To decipher their messages, huge telescopes are required: volumes of several cubic kilometers of ice or water, instrumented with thousands of light sensors. The sensors capture the light trail created by the collision of a neutrino with a water molecule, enabling scientists to determine the energy and direction of origin of the neutrino. Prof. Elisa Resconi recently launched an initiative to develop a new observatory for cosmic neutrinos in the Pacific Ocean, the Pacific Ocean Neutrino Experiment (P-ONE). Within the ERC-funded NEUTRINOSHOT project, the first telescope module with three strings, each 1000 meters long, will be installed off the coast of Canada at a depth of 2.6 kilometers.

Elisa Resconi is Liesel Beckmann Professor for Experimental Physics with Cosmic Particles at TUM, spokesperson of SFB 1258 “Neutrinos and Dark Matter in Astrophysics and Particle Physics” and a member of the Cluster of Excellence ORIGINS.

Prof. Dr. Fabian Theis (Mathematics)

Molecular cell biology aims at understanding cells and their reaction to external signals. Single-cell genomics enables researchers to read out the internal state of a cell in unprecedented detail. In his ERC-funded project “DeepCell”, Fabian Theis will develop mechanism-constraint machine learning approaches for single-cell genomics to systematically model a cell’s behavior under external perturbations, focusing on the largely-untouched area of drug-induced perturbations with single-cell readouts. If successful, it will allow optimal treatment predictions in new cell types. DeepCell thus opens up the possibility of in silico drug screens, with the potential to expedite drug discovery and impact clinical settings.

Fabian Theis is Professor of Mathematical Modelling of Biological Systems at TUM and Director of the Institute of Computational Biology at Helmholtz Munich.  In 2010 he was awarded an ERC Starting Grant.

Further information and links

Technical University of Munich

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