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Field
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, fairness). Provenance and integrity of machine learning pipelines. Generative content authenticity. Cyber-physical machine learning systems. Scalability of properties from small to large models. In
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. For example, anaerobic bacteria culture and human cell co-culture infection models; cell viability assays and cancer invasion and migration assays; ELISA, quantitative PCR, DNA damage assays
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-specific TEM protocol will be used to reveal their subcellular localisation. This work will be done at UEA and IOCAS (Prof. Shan Gao). Objective 2: Using the genetically tractable model diatom Phaeodactylum
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cutting-edge molecular techniques and generate gene knockouts to identify new enzymes and pathways involved in this process. Finally, the PGR will utilise plant infection models and high-resolution
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: adapting existing models of bird movement and migration to test hypotheses about the ecological processes shaping observed connectivity patterns. Identify species and populations that have the highest
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observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
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the optimization-based methods (doi.org/10.1016/j.apenergy.2020.116152 ), 3- Weakness of the model-predictive-control (MPC) against HESS’s parameters uncertainties, noises, and disturbances (doi.org/10.2514/6.2022
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, understand, characterise, and model the effect of surface roughness on wall turbulence when out of equilibrium. Particular emphasis will be made on determining if any form of flow similarity exists across
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grade. Generate data through comprehensive laboratory grinding tests on various rail grades to train and validate the ML model. Utilise numerical modelling to establish acceptable thresholds for surface
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will be required to demonstrate their ability to identify fundamental flow features and model these using suitable CFD methods. Experience in Fortran/C/C++/Python/Matlab is an advantage but not essential