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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
40 research groups and some 1,000 employees from over 50 nations, it is the largest institute of the Max Planck Society. The Department of Theoretical and Computational Biophysics headed by (Prof. Dr
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limited understanding of how tumors systemically impair immune responses. Meanwhile, traditional animal models often fail to capture the complexity of human immune-cancer interactions. This position
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from over 50 nations, it is the largest institute of the Max Planck Society. The Department of Theoretical and Computational Biophysics headed by Helmut Grubmüller is inviting applications for a PhD
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
Biocomplexity (LFPB), headed by Prof. Dr. Eberhard Bodenschatz, fosters a stimulating international research environment on active complex systems ranging from Biophysics to Fluid Dynamics. The research
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Your Job: Develop techniques to simulate, control, and optimize the time-dependent dynamics for increasing system complexities Implement and optimize small quantum circuits on super- and semi
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, ocean, marine ecosystem, and impact models of different complexity and will include both traditional and new ocean modelling approaches with the final objective of delivering: (i) coordinated and
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consortium SynThera funded by the Carl Zeiss Foundation (www.synthera.eu/ ). We are seeking an excellent and enthusiastic post-doctoral researcher with a strong interest in computational microbiome research
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
. The Research Atmospheric clouds and aerosols are major sources of uncertainty in weather and climate prediction due to their complex, multi-scale nature — from nanometers to hundreds of kilometers. Turbulence
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s