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for this post. The successful candidate will be required to develop a personal research programme in theoretical cosmology (which may include numerical modelling and/or data analysis), interacting with faculty
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permeability selection in variant membrane chemistries. This work will run in parallel to experimental analysis conducted at the University of Exeter using synthetic vesicles to observe permeability
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. The research will involve both analytical work and numerical computations. The balance between analytical and numerical type work is flexible and can depend on the preferences and skills of the successful
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atmospheric physics, meteorology, climate, numerical methods, and data science. The Research Associate will be proficient in programming/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script
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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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effects. You will contribute to the numerical modelling part of the project, which will benefit from novel element level and centrifuge testing experimental results. You will set up and validate numerical
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to enable robust robot autonomy in complex, real-world environments. The post sits within our EPSRC Programme Grant in Embodied Intelligence and will advance the state of the art in localisation and scene
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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to