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matter and smart materials? Then come and join our team as a PhD candidate! Materials that spontaneously ’morph their structure and optimise themselves to particular functions will open entirely new
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Sciences, Pedagogics or a related discipline. You have strong analytical skills and experience with complex quantitative analytical methods (e.g. multilevel and/or structural equation models). You are
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of this state-of-the-art facility, which is expected to be fully operational by 2035/2036 and will include advanced laboratories for diagnostics and research, cutting-edge biosafety systems, and complex technical
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and/or Python. Experience in, and aptitude for, complex statistical modelling (inc. mixed effects regression models and/or Bayesian statistics). Excellent written and spoken English. Desirable (traits
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approach is to apply foundational techniques grounded in logic, semantics, and verification. This work takes place within the CYCLIC project: Cyclic Structures in Programs and Proofs, a collaboration among
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specific ownership types. The responses of firms with different ownership types to geopolitical changes, navigating the new complexities of international business. The role of different types of owners
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with different ownership types to geopolitical changes, navigating the new complexities of international business. The role of different types of owners on the formation, evolution, and long-term success
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-world networks with different structural properties. During the PhD, the successful candidate will work on several subprojects and analyse random graph models and complex networks by probabilistic tools
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the static structure of proteins have become invaluable tools for biologists and medicinal chemists, machine learning-based prediction of protein dynamics is still in its infancy. An additional challenge is
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develops guidelines. She also leverages complexity theory in connecting experts in a range of disciplines to work together on practical methods for application in medical research and guideline development