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and the safety implications arising from these interacting processes. You will use and extend PyBaMM, which is an open-source Python-based battery modelling framework (https://pybamm.org
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. - Experience with clinical or biological datasets. - Practical experience with Python and SQL. - Knowledge of wearable, molecular and health data. - Knowledge of research methods and statistical procedures
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being undertaken in collaboration with UCL, King’s College London and University of Westminster. The project’s aims include dRTP community development, enhancing career pathways and structures and
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journals Knowledge of hydrological data collection, curation, and analysis Ability to conduct a detailed review of recent literature Advanced computer skills including scientific data analysis (e.g., Python
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or Python to clean, process, and analyse data Supporting the development of structured datasets suitable for analysis and visualisation Assisting with structured analysis of both numerical and text-based data
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maintaining well-organised datasets that can be queried, analysed, and used in downstream applications Writing clear, reproducible code in R or Python to clean, process, and analyse data Supporting
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transcranial ultrasound. Assist with physiological monitoring during MRI scanning. Learn to analyse data with standard scientific analysis software (R, Python, Matlab). A first or 2:1 degree, or a masters, in a
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computing (e.g. Python, C/C++, Fortran, MATLAB). Ability to analyse and interpret complex datasets, with good scientific judgement and attention to detail. A motivated, collaborative researcher with strong
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. Objectives: Using our in-house python-based nonlinear aero-thermo-structural finite element solver you will investigate, understand, and optimise the behaviour of flight structures subjected to relatively
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of computational modelling techniques in healthcare or biomedical sciences, and in programming languages such as Python or Julia. Experience working with medical imaging in a research environment and proficiency in