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methods based on machine learning, and developing and applying simulation methods and models for equilibrium and nonequilibrium molecular dynamics simulations. You will model meta-lactamases enzymes
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supervise graduate students. Mentor graduate students in modeling and data analysis using machine learning. Guide students in developing coding skills using the latest AI models. Host regular individual and
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to operationalize machine learning and artificial intelligence models. This may include model deployment and leveraging LLMs through agentic workflows. Document engineering work: Document and share details
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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and
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for managing and versioning many models in various different projects. Your qualities You have completed a Master's degree in 3D modelling, game design or human-computer interactions, and you have knowledge
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candidate with expertise in statistical learning and machine learning, both theoretical and computational. Minimum Education and Experience Ph.D in a related field. Preferred Education and Experience Other
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; experience with signal processing, spectral analysis, time-series analysis, machine learning algorithms and the modeling and analysis of complex systems; strong publication record; proficiency with either
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) and AI models of detection and intervention (e.g., machine learning, large language models, neural networks). To offer a few examples, this hire could focus on supporting developmentally diverse
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems