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to study chromatin and gene regulation in mammalian cells and human disease systems. Current ongoing projects include: statistical modeling and advanced machine learning/AI method development for predicting
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. Combining AI-based prediction (e.g., TCNN, LSTM, etc) with musculoskeletal models to estimate and predict muscle activation and tendon force over short horizons (e.g. ~200 ms). Integrating these predictions
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are analysed using big data and business intelligence applications to monitor tourisms. Additionally, predictive modeling methods are applied to estimate tourist mobility behavior and movement patterns between
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work on research projects employing latent variable modeling and risk prediction methods to better understand substance use related morbidity and mortality outcomes (e.g., overdose, hospitalization
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evaluating and piloting new technologies to improve team workflows and research quality. Experience implementing or using AI, predictive modeling, or advanced analytics to inform prospect identification and
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learning (AI/ML) being a major focus. Many of the laboratory's interests center around the identification of small molecules using mass spectrometry data, and the use of language models to predict
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of pharmaceutical formulation and manufacturing processes. The role The post holder will develop and implement mechanistic models to analyse and predict the behaviour of pharmaceutical processes. Your work will
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, to create a responsible and innovative university to serve as a model for the 21st century. Within ICN, the ChemSenSim group (https://lab.chemsensim.fr/ ) develops interdisciplinary research projects
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are developing methods and tools to explore and understand immunity across domains of life, from genomics to experimental work in various model organisms. The role of the engineer will be to consolidate, update
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. We use advanced computational technologies to discover how biomolecules and organisms function and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases