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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models
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learning and advanced statistical modeling * Proficient programming skills in Python and/or R, experience with machine learning and omics analysis libraries (e.g., scikit-learn, TensorFlow/PyTorch
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have an opportunity to develop their leadership skills on projects related to advancing natural plant-derived compounds and/or repurposing clinically-approved drugs for indications related to wound
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used to assess transfer of pathogen loads to fruits and vegetables. The microbial community changes and its influence on pathogen levels will also be quantified. These data will fit into models
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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models
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development, patents, and publications. The successful applicant will have an opportunity to develop their leadership skills on projects related to advancing natural plant-derived compounds and/or repurposing
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connectivity of the broader community, training, networking, as well as state-of-the-art research. This post will develop artificial intelligence methods for the prediction of crystal structure, the critical
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, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: i. Develop, train, and optimise deep learning models for object
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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connectivity of the broader community, training, networking, as well as state-of-the-art research. This post will develop artificial intelligence methods for the prediction of crystal structure, the critical