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team from various backgrounds with a large knowledge base. We conduct research on Li-Ion batteries ranging from material development, structural analysis with x-ray techniques, to digital modeling and
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Systems We have an open PhD position at the intersection of machine learning, embedded intelligence and human–computer interaction. The project will explore how learning systems can become more adaptive
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Your position Biomolecular dynamics, such as conformational changes, are the understudied link between biomolecular structure and function. Single-molecule FRET is an established technique, unique
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: Design and implement specific functional read-outs and quantitative assays to assess vascular-lymphatic interactions. Collaboration & dissemination: work closely with research partners, contribute
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machine learning Write research papers, articles, and present results at leading international conferences. We publish in venues such as ICML, NeurIPS, ICLR, JMLR, AISTATS, and more Interact with national
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niches. Building on our experience in cell-fate tracking tracking and studying various stages of the metastatic cascade, we set out to follow tumour cell-niche interactions to reveal how distant sites
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Perform experiments in PSI laboratories and at synchrotron radiation facilities, data processing and analysis Optimization and automation of reaction parameters, correlation of the structural data with
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of printed biosensors while the other will address the embedding of sensors in 3D printed fluidic micro-structures. Context This project is funded in the framework of the Swiss National Science Foundation (SNF
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in the global carbon cycle and have the potential to mitigate greenhouse gas emissions by oxidizing methane, even at atmospheric concentrations. The research will investigate how interactions between
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interactions and their integration with wider energy networks. Your tasks The focus of this research is to design and develop (physics-informed) hierarchical graph neural network architectures that can capture