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Stewards from UCL ARC). Convert pre-processed data into features suitable for computational statistics and machine learning analyses of neurodegenerative disease progression. The salary range for this post
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programming such as Python, R, MATLAB, or other similar programs and experience in using simulation/optimisation models and advanced data handling techniques e.g. machine-learning techniques, statistics
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, b) computational modelling, or c) machine learning. This is a complex project managing longitudinal data from a range of sources. Therefore, thoroughness and attention to detail while managing
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modelling, machine learning, growth mixture modelling). Excellent skills in statistics and advanced quantitative data analysis, including strong skills in command driven programming languages (e.g., STATA, R
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effectiveness and safety. This PhD project aims to address this challenge through biomimetic engineering design, combining predictive in silico modelling with machine-learning techniques and microfluidic
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Mattelaer, Christophe Ringeval). Research activities in include SM and BSM aspects of collider physics (LHC and future colliders, simulation tools, machine learning, effective field theories, amplitude
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Partnership between UCL and AstraZeneca and to work as part of a cross-disciplinary team across both sites (London and Cambridge). This post is focused on the use of machine learning models of protein
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in securing research funding is essential, as is demonstrable expertise in complex modelling techniques such as machine learning, network neuroscience, or related computational approaches. You will
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical technology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess