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insights. Second, starting from large-scale transnational infrastructures that connect peripheries to various centres reveals the complexity of political-economic integration and dependencies better than
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executes experiments of considerable scope and complexity in the assigned research lab; collects and analyzes data for research sponsored by appropriate agencies and Institutions; identifies and selects
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working with large or complex datasets, ensuring accuracy, reproducibility and secure data management. They will be able to work both independently and collaboratively as part of an interdisciplinary team
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focused on creating integrated biological systems capable of autonomously performing useful tasks and elucidating design principles for engineering complex cellular and tissue phenotypes. Will work closely
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the behaviour of the complex zeros of (classes of) these polynomials. The behaviour of the zeros is closely connected with the algorithmic tractability of (approximately) evaluating these polynomials and
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key responsibilities will be to: work on an ARC DP project aiming to develop of hybrid asymptotic methods based on exponential asymptotics and computational complex analysis apply these methods
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Discovery Early Career Researcher Award (DECRA) Fellow, whose work spans advanced AI, cyber-physical systems, and the science of large-scale infrastructure and organisational complexity. This research stream
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mathematical, statistical, and machine-learning-based analysis of complex data sets, such as hypothesis testing, supervised/unsupervised learning, linear models, etc. Experience with atlas-scale single-cell data
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the effects of these factors at the tissue level. The position will also involve simulating and optimizing complex models that integrate biological and physical data using advanced methods, such as physics
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, focusing on the structural characterisation of macromolecular complexes in bacteriophage replication initiation, will be carried out in collaboration with Dr Indrajit Lahiri at the School of Biosciences