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Field
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tasks involve the detection, discrimination, and interpretation of coloured signal lights and information presented on modern digital cab displays. The project will combine visual task analysis, spectral
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also include preparation of food samples, extraction and analysis of target and non-target compounds, processing of large HRMS datasets, data analysis, statistical evaluation, collaboration with
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collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI
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training programme at the start of the PhD to develop skills in areas such as programming, data analysis, machine learning and signal processing. This will provide the technical foundation required to work
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evaluate machine learning and statistical models Assist with experiment tracking, result analysis, and reproducibility Use data visualization tools to visualize data analysis and learning results Contribute
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their own vehicle and find their own housing for the duration of the position. QUALIFICATIONS Knowledge of computer programming language(s) for data analysis and visualization Knowledge of spreadsheet
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through multi-modal sensing, autonomous UAV platforms, and advanced AI-based analysis. A central focus is the detection of defects in bridges and viaducts using X-ray, LiDAR, visual and acoustic data
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to collaborative project across teams within our Center, as well as joined initiatives with external academic and industrial partners Data analysis, interpretation, visualization and integration Keeping an industry
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should have documented background in the following areas: Electrodynamics Data analysis for scientific applications Programming (e.g., Matlab, Python, C, C++) for scientific applications Previous
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should have documented background in the following areas: Electrodynamics Data analysis for scientific applications Programming (e.g., Matlab, Python, C, C++) for scientific applications Previous