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computational model to capture the complex transport of gases, liquids, and charges in these porous structures, including the complex interfaces between them. Insights from the model will directly guide the
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affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from
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the chemical structure alone. Once established, we will expand the self-driving labs to measure more complex properties such as foaming, phase separation or particle formation, and fine-tune our AI models. In
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/en/jobs/354372/phd-position-spines-modelling-t… Requirements Specific Requirements Highly motivated students with a MSc in construction engineering and management, complex system engineering and
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want to contribute to the next level of self-driving labs? Are you excited about the application of high-throughput experiments to train AI tools to predict properties of complex mixtures? Then join our
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. Typically, the specificity, speed, and directionality of transport are tightly woven into the ordered structure of the pore which is characterized by a limited conformational flexibility. Remarkably, nature
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, speed, and directionality of transport are tightly woven into the ordered structure of the pore which is characterized by a limited conformational flexibility. Remarkably, nature also offers a fascinating
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Airport). Your profile Highly motivated students with a MSc in construction engineering and management, complex system engineering and management, public policy and engineering, technology management
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sites, collecting and identifying specimens, and analysing 3D flight trajectories in relation to local environmental cues such as light intensity, wind conditions, and visual structure. A key focus will
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relation to local environmental cues such as light intensity, wind conditions, and visual structure. A key focus will be on how Dipteran insects perceive and use these cues—especially visual landmarks and