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and enabling commercial deployment. The work will integrate model based design of experiments, machine learning, hybrid and kinetic modelling (digital twin development), process design, simulation and
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Join our dynamic, multidisciplinary team as a Research Associate and make a transformative impact in scientific machine learning and digital twins for healthcare innovation! This role focuses
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behavioural, physiological, and environmental acoustic variables. This post would suit someone with a PhD in biomedical engineering, data science, machine learning, experimental psychology, audiology, cognitive
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, and passively collected data such as geolocation. The model will be dynamic (updating predictions as patients record new data), and will consider statistical and machine learning algorithms. Development
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opportunity to work at the intersection of multimodal AI, cancer biology and digital pathology. The successful applicant will have a PhD or MSc with a significant machine learning element and/or experience with
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machine learning, agent-based modelling and multi-criteria decision analysis. Excellent scientific writing, team work, organisational skills and communication skills with a range of stakeholders are