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costs of their project. We will support two students, one in the area of health data science/epidemiology/statistics and the other specialising in applied machine learning and informatics. The closing
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frameworks (MOF), a reticular class of materials for their use as excipients. The project also involves elements of machine learning models for screening appropriate excipients from FDA data base. Person
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more than one year (or part-time equivalent) are NOT eligible to apply for an award. Recommended reading https://www.england.nhs.uk/2019/06/nhs-aims-to-be-a-world-leader-in-ai-and-machine-learning-within-5
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on recent developments in computational polymorph prediction and nucleation modelling that benefit from synergies between statistical mechanics, machine learning and computational chemistry, and will develop
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or electronic engineering, machine learning, medical physics or neuroscience. Knowledge of electronics is essential. Strong programming skills (MATLAB is essential) & Phyton (TensorFlow library, desirable
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capability in natural language understanding and generation. Conversational systems or dialogue systems are useful in supporting interactive information exchanging, especially between human and machines
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and collaborate with a strong multidisciplinary team of academics at University of Southampton and experts from University College London. Person specifications: Master degree in machine learning