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patient clusters and digital phenotypes, leveraging machine learning approaches to identify individuals at high CV risk based on clinical and biochemical markers, immune markers, digital health data (e.g
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, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to collaborating with researchers from other disciplines. The successful candidate will
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of the project is to use machine-learning assisted molecular dynamics simulations incorporating quantum effects for the identification of new variant-specific drug targets which will be validated experimentally
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