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modelling and finite-element simulations of multicomponent, multiphase electrochemical systems. Ability to manage own academic research and associated activities Previous experience of contributing
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and experience: Essential criteria PhD in bioinformatics, computational biology, or a related discipline * Extensive experience and expertise in analysing/ training models on biological or chemical
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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people from non-technical backgrounds Experience with developing or deploying light weight models in environments with restricted resources (e.g. outside of HPC environments) Downloading a copy of our Job
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- Develop original numerical methods for facility simulation in presence of expansion waves - Demonstrate improved estimates of rate constants for two-temperature models - Contribute
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theory, and/or (ii) an application focus in radio astronomy or magnetic resonance imaging, including both simulation and real data processing expertise. Competence in specific algorithmic approaches
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structural development over time at the group, sub-group, and individual level (e.g., using normative modelling and clustering approaches to parse heterogeneity). The candidates will further have the
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the control and stability of quantum operations. Using advanced Multiphysics simulation tools, the researcher will create models of the physical and control architecture, enabling the identification of design
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structural development over time at the group, sub-group, and individual level (e.g., using normative modelling and clustering approaches to parse heterogeneity). The candidates will further have the