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Field
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any
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will benefit from Lonza’s expertise and technology within peptide T cell immunogenicity, and the vast expertise within immunoinformatics and machine learning models at DTU to address this challenge
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health and translational medicine using a "bench-to-bedside" approach. By harmonising and analysing diverse biomedical data, while focusing on the secure data processing and predictive modelling, we aim
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Interest in analyzing biomedical/clinical/genomics datasets using computational approaches such as longitudinal analysis, mixed-effect modeling, regression, and AI/machine learning in large-scale electronic
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-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine learning is desired
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labs at Stanford to tackle emerging clinical questions in oncology, utilizing various AI methods, predictive modeling approaches, and large language models. Specific areas of interest include but are not
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disparities for communities and populations. Candidates will receive mentorship and training in precision health, including advanced statistical methods focused on predictive modeling in relation to response
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, establishment of a seagrass farm, and monitoring of a large living shoreline project. In addition to research, the post-doctoral scholar will be required to teach a 4-5 week-long field course each spring semester
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modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process
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phenotypic, genotypic, and environmental data to build prediction models for key traits of blueberry such as flowering time, yield, and fruit quality. This position reports to Dr. Sushan Ru at Auburn