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orientation with compositional design, the project will investigate how directional control over framework domains influences charge transport, optical response, and catalytic performance. Applications include
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possess proven expertise in performing theoretical research in the fields of theoretical high-energy physics and quantum field theory as well as theoretical quantum information, as proven through a
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experimentation and training. Science of Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers of model performance at scale. As an early member of this fast-growing team
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be an advantage: Programming and data analysis experience Experience with working on high-performance computers What we offer: Research freedom: Develop your own ideas within the project’s broad scope