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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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: solar magnetic field modelling, computational fluid dynamics, or solar observational data analysis. Working knowledge of at least one scientific computing environment (e.g. Python, Fortran, Matlab, C
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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focus on the development of new theoretical frameworks, implementation of new methods in first principles computational modelling packages, and direct application to representative solid state systems
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areas include: • Investigate innovative financing models for circular bioeconomy businesses and value chains, such as food, fashion, and health. • Explore non-market mechanisms
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for our state of the art sport and gym facilities and access to a 24-7 Employee Assistance Programme. • On site nursery is available plus access to holiday camps for children aged 5-16. • Family
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classification and the modelling of neuron and circuit function. Data sources will be neuronal morphologies, connectivity and computationally inferred or manually annotated metadata and published experimental data
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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neurodegenerative brain disorders. The successful applicant will be responsible for the development and characterisation of in vitro models recapitulating RNA binding protein deficiency in brain disorders, as