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part of the Structural Genomics Consortium (SGC) Target 2035 Initiative, a global collaboration in the area of protein science, machine learning and data science towards improving our ability to predict
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-centric machine-learning frameworks for large-scale sequence-structure analysis and functional prediction. The role involves designing, implementing, and benchmarking computational models; developing and
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second in the UK for research power and first in England. About the role The project will be carried out at the Department of Computer Science, in the Machine Intelligence Lab (https
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/drc/ ). About the role The role will contribute to on-going research at the UCL Hawkes Institute to develop advances in computational modelling of neurodegenerative disease, machine learning, and big
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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
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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