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the properties of composite, biological networks which consist of stiff filaments and liquid inclusions which arise from liquid-liquid phase separation. We will use a multi-scale approach bridging scales from
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instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Netwon`s method. In particular, we aim to develop a neural network architecture that will allow us
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addition, the dynamics and transport processes across the UTLS adds complexity to unveil the role of UTLS aerosols in cirrus formation and the life cycle of cirrus. Therefore, it is crucial to measure
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particle physics. In all of these areas, methodological development through machine learning is taking place — for example, in predicting the evolution of complex molecular systems over long timescales
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from multiple disciplines to address complex research questions that require an interdisciplinary approach. Shape your scientific journey in fields such as molecular and cellular biology, genomics and
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implement computational frameworks for processing, integrating, and analyzing large-scale phosphoproteomics patient data, supporting the discovery of signaling networks and actionable therapeutic targets in
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Associate / PhD Student (m/f/x) within the MSCA Doctoral Network SLICE (due to funding, the salary is calculated according to MSCA regulation) starting October 1, 2026. The position is limited to 36 months
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such as 3D tissue imaging, molecular profiling are combined with AI tools to decode the complexity of tissues and shed light into cancer biology. Our interdisciplinary team — comprising biologists
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technologies for batteries. Your tasks in detail: Develop innovative quantum computing approaches for the simulation of electrochemical processes in complex electrode materials Connect quantum-enabled models
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for complex microbial communities and their interactions with potential interventions. Currently, we are seeking a PhD candidate to support our interdisciplinary team. Be part of change You will conduct a