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environments, and distributional shifts. The research will combine probabilistic modelling, network-based representations, and modern AI methods to enable scalable and interpretable decision-making in complex
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, brain circuit imaging and atlas mapping, and research software engineering - studying the brain circuits underlying craving, reward, and addiction. The hire will develop ML/AI methods for an integrated
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and Psychology’ led by István Zoltán Kiss and Andreia Sofia Teixeira at the Network Science Institute, Northeastern University London. Human behaviour during epidemics reflects our nature as socially
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further appears in the approximation of various dynamical problems by tensor networks and neural networks. In all these cases, the parametrization is typically irregular, meaning that the occurring linear
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transcriptomics) in conjuction with intravital imaging and proximity labelling tools to define the dynamic interaction of immune cells in cancer. The candidate will need to master both complex 'wet lab' techniques
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built in the commercial finite element software ‘Abaqus’ to capture pellet clad interaction in both light water reactors (LWRs) and the UK advanced gas cooled reactor (UK-AGR). Whilst Abaqus offers
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findings will be valuable, as the work will define the physical and engineering limits of the approach. If successful, the underlying measurement principle could have wider relevance to future cardiovascular
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Response or Security Operations organization. Demonstrated technical proficiency with modern computing hardware, software, and networking technologies. Experience conducting research and publishing academic
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modern machine learning, statistical signal processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs
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start on 1st January 2027. Project Description Plastic pollution is one of the defining environmental health challenges of our time. Micro- and nanoplastics (MNPs) contaminate the air we breathe