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and flow field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision
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experience in atomistic simulations and catalysis is an advantage. Our offer We offer a stimulating, multidisciplinary research environment within the ETH Domain, where communication and interaction to create
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single cell sequencing approaches. Analysing and visualizing high-dimensional data. Engineering of T cell receptors with CRISPR-Cas9. Testing B and T cell priming conditions in organoids and mouse models
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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
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interviews on site. Shortlisted candidates will be invited to the FMI to present their scientific interests, discuss with recruiting group leaders, and interact with group members and current PhD students
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functional states along the activation pathway Investigate ligand-dependent modulation of receptor states Study receptor interactions with effector proteins The successful candidate will work in a highly
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for participant interactions Capacity for self-directed work within an interdisciplinary team Excellent written and oral communication skills in English and German Ability to work independently and collaboratively
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key contributions to novel personalized strategies of particles design for drug delivery, imaging, or diagnosis. Characterize, understand, the interaction of particulate materials with cells or tissues
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, wind turbine rotor blade aerodynamics, gust interactions, and fluid-structure interactions. The research focuses on unfolding the origin and development of unsteady flow separation and vortex formation