Enhancing computational astrophysics with interpretable machine learning
Focus topic: | Artificial Intelligence |
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Type of funding: | Individual funding programmes |
Programme: | CZS Nexus |
Funded institution: |
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Tobias Buck holds a doctorate in astrophysics. During his studies at the University of Heidelberg, he focused on robotics, machine learning and space exploration. Most recently, he worked as a postdoc at the Leibniz Institute for Astrophysics in Potsdam.
Goals
The aim of the research project is to develop innovative computational methods from the synthesis of physical laws and machine learning.
In an international, interdisciplinary team of scientists, modern machine learning methods are combined with high-resolution computer simulations to gain new scientific insights into the formation of galaxies.
With his research group at the Interdisciplinary Centre for Scientific
Computing and the Centre for Astronomy in Heidelberg, Dr. Tobias Buck would like to advance astrophysics and make machine learning algorithms more robust and interpretable.
Involved persons:
Dr. Tobias Buck
Universität Heidelberg
Detailed information:
Focus topic: | Artificial Intelligence |
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Programme: | CZS Nexus |
Type of funding: | Individual funding programmes |
Target group: | Junior research group leaders |
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Funding budget: | 1.499.000 € |
Period of time: | August 2022 - Juli 2028 |