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PhD Candidate, you will develop new analytical theories and methods for complex systems of partial differential equations and apply them to models for marine biofilm growth. Join a stimulating research
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energetic constraints on circuit function. Deriving design principles for neural networks performing complex tasks. We employ computational and analytical methods from applied mathematics and physics
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(on Ecological Momentary Assessment [EMA] data), aiming to develop new ways to quantify fast and slow fluctuations of fatigue in real life, based on complexity theory. Then, you will co-design and conduct a study
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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