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with excellent English proficiency to explore this fascinating intersection of experimental physics, machine learning, and complex systems. A background in optical microscopy and machine learning is of
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hydrological community. Alternatively, it is well known that Neural ODEs [2] are capable of representing dynamic systems that are coded in ODEs. They can encapsulate the complex temporal dependencies and
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, biophysical and bio-chemistry, theoretical chemistry and mathematics , to advance the understanding of the emergence of complexity in molecular systems. Our RTG combines science and research projects that start
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& Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and opinion dynamics. Our goal is to gain a deeper understanding of
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. Transition metal-based complexes, in particular, offer rich spin properties that can be tailored through ligand design. This project aims to explore and optimize such molecules to enhance their performance as
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arbitrary complexity and shape at the sub-nanometer scale. Such structures can be used to construct artificial cell mimics and new materials. A scaffold-free DNA tile assembly is a programmable method for the
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Description Conducting research for a changing society: This is what drives us at Forschungszentrum Jülich. As a member of the Helmholtz Association, we aim to tackle the grand societal
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Description Conducting research for a changing society: This is what drives us at Forschungszentrum Jülich. As a member of the Helmholtz Association, we aim to tackle the grand societal
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Description Glyphosate is the most widely applied herbicide on Earth and accounts for 92% of the herbicide global use (Antier et al., 2020). In Europe, 25 – 64% of annual crop acreage was treated
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Description Conducting research for a changing society: This is what drives us at Forschungszentrum Jülich. As a member of the Helmholtz Association, we aim to tackle the grand societal