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) to discover multi-modal biomarkers, immune-microbe interaction modules, and spatially localized signatures associated with disease outcomes. • Develop novel AI-driven frameworks to predict clinical phenotypes
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, to enable a transition from responsive maintenance interventions/renewals, to predictive, proactive, and targeted ones that help to avoid failures. By integrating numerical simulations, probabilistic
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, perform cutting-edge analytical techniques for causal inference and prediction, and writing papers for both an academic audience and for practitioners (managers and/or policymakers). Desired Qualifications
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CRISPR/Cas9 approach) to manipulate selected genes of interest recently confirmed or predicted to be involved in different types of neurodegenerations. The candidate will further use the developed model
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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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position is funded by multiple NIH projects, e.g., https://tinyurl.co m/ysxhmujvThe overall goal is to : (1) develop inference and dynamic prediction models using a wide variety of data, including clinical
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processes. Carbonate biomineralisation is a key process in global carbon cycling, but there are major gaps in our understanding of how biominerals form. We lack a quantitative understanding that can predict
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following areas: (1) first-principles thermal or optical property prediction (2) thermal property measurement, (3) near-field optical phenomena, (4) thermophotovoltaics. • The ability to communicate expertly
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industry and academia, including experts on system services, converter control, flow propagation and lidar-based predictions. Among others, your tasks will comprise: Development of control algorithms
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Biological Insights in Preclinical Glioma ModelsMulti-modal machine learning for predicting Glioma progressionHealthAEye: Deep Learning for Retinal Image Analysis and Disease Monitoring *Life Sciences:Germs